You will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work with different research teams and squads across multiple areas led by our Director of Science, Prof. Vittorio Ferrari, and directly impact our solutions that are used worldwide by over 55,000 businesses.

If you have seen the full ML lifecycle from ideation through implementation, testing and release, and you have a passion for large data, large model training and building solutions with clean code, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.

Mountain View

Who we are Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly.

Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale

Where you will have an impact We are looking for an experienced Research Engineer to help us in our journey to scale end-to-end neural networks for autonomous driving. You’ll be working across our research team to build, integrate, test and scale algorithms, tools, and machine learning solutions for autonomous driving.

What you will bring to Wayve 5+ years of software engineering experience in an industrial research environment Passion to work in a team on research ideas that have real world impact Strong software engineering experience in Python and other relevant languages (especially C++ and CUDA) Ideally with direct experience working in at least one of computer vision, robotics, simulation, graphics, large language models Ideally with several years working on large-scale machine learning algorithms and systems BS, MS, or above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience

What we offer you The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact Competitive compensation Fully employer-covered medical, dental and vision insurance! Further benefits such as catered lunch, yummy snacks, and variety of drinks, life insurance, employer contributed retirement account, therapy, yoga, office-wide socials and much more. A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day This is a full-time role based in our office in California. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We also operate core working hours so you can be where you need to be for family and loved ones too. Teams determine the routines that work best for them.

Location Madrid, ESP

Description At Amazon, we are committed to being the Earth’s most customer-centric company. The International Technology group (InTech) owns the enhancement and delivery of Amazon’s cutting-edge engineering to all the varied customers and cultures of the world. We do this through a combination of partnerships with other Amazon technical teams and our own innovative new projects.

You will be joining the Tools and Machine learning (Tamale) team. As part of InTech, Tamale strives to solve complex catalog quality problems using challenging machine learning and data analysis solutions. You will be exposed to cutting edge big data and machine learning technologies, along to all Amazon catalog technology stack, and you'll be part of a key effort to improve our customers experience by tackling and preventing defects in items in Amazon's catalog.

We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading machine learning solutions. We strongly value your hard work and obsession to solve complex problems on behalf of Amazon customers.

Excited to see you at CVPR! We’ll be at booth 1404. Come see us to talk more about roles.

Our team consists of people with diverse software and academic experiences. We work together towards one common goal: integrating the software, you'll help us build into hundreds of millions of vehicles.

As a Research Engineer for Optimization, you will focus on research and development related to the optimization of ML models on GPU’s or AI accelerators. You will use your judgment in complex scenarios and apply optimization techniques to a wide variety of technical problems. Specifically, you will:

• Research, prototype and evaluate state of the art model optimization techniques and algorithms
• Characterize neural network quality and performance based on research, experiment and performance data and profiling
• Incorporate optimizations and model development best practices into existing ML development lifecycle and workflow.
• Define the technical vision and roadmap for DL model optimizations
• Write technical reports indicating qualitative and quantitative results to colleagues and customers
• Develop, deploy and optimize deep learning (DL) models on various GPU and AI accelerator chipsets/platforms

Location Multiple Locations

Description

Members of our team are part of a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems. Our members contribute technology deployed worldwide by partnering with our business teams across mobile, compute, automotive, cloud, and IOT. We also perform and publish state-of-the-art research on a wide range of topics in machine-learning, ranging from general theory to techniques that enable deployment on resource-constrained devices. Our research team has demonstrated first-in-the-world research and proof-of-concepts in areas such model efficiency, neural video codecs, video semantic segmentation, federated learning, and wireless RF sensing (https://www.qualcomm.com/ai-research), has won major research competitions such as the visual wake word challenge, and converted leading research into best-in-class user-friendly tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet). We recently demonstrated the feasibility of running a foundation model (Stable Diffusion) with >1 billion parameters on an Android phone under one second after performing our full-stack AI optimizations on the model.

Role responsibility can include both, applied and fundamental research in the field of machine learning with development focus in one or many of the following areas:

• Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. large language models, deep generative models (VAE, Normalizing-Flow, ARM, etc), Bayesian deep learning, equivariant CNNs, adversarial learning, diffusion models, active learning, Bayesian optimizations, unsupervised learning, and ML combinatorial optimization using tools like graph neural networks, learned message-passing heuristics, and reinforcement learning.

• Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for model compression, quantization, architecture search, and kernel/graph compiler/scheduling with or without systems-hardware co-design.

• Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, causal and language-based reasoning.

• Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond. The use cases can broadly include computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design

• Design, develop & test software for machine learning frameworks that optimize models to run efficiently on edge devices. Candidate is expected to have strong interest and deep passion on making leading-edge deep learning algorithms work on mobile/embedded platforms for the benefit of end users.

• Research, design, develop, enhance, and implement different components of machine learning compiler for HW Accelerators.

• Design, implement and train DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).

Seattle, WA; Costa Mesa, CA; Boston, MA

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

THE ROLE We build Lattice, the foundation for everything we do as a defense technology company. Our engineers are talented and hard-working, motivated to see their work rapidly deployed on the front lines. Our team is not just building an experiment in waiting, we deploy what we build on the Southern border, Iraq, Ukraine and more.

We have open roles across Platform Engineering, ranging from core infrastructure to distributed systems, web development, networking and more. We hire self-motivated people, those who hold a higher bar for themselves than anyone else could hold for them. If you love building infrastructure, platform services, or just working in high performing engineering cultures we invite you to apply!

YOU SHOULD APPLY IF YOU: -At least 3+ years working with a variety of programming languages such as Rust, Go, C++, Java, Python, JavaScript/TypeScript, etc. -Have experience working with customers to deliver novel software capabilities -Want to work on building and integrating model/software/hardware-in-the-loop components by leveraging first and third party technologies (related to simulation, data management, compute infrastructure, networking, and more). -Love building platform and infrastructure tooling that enables other software engineers to scale their output -Enjoy collaborating with team members and partners in the autonomy domain, and building technologies and processes which enable users to safely and rapidly develop and deploy autonomous systems at scale. -Are a U.S. Person because of required access to U.S. export controlled information

Note: The above bullet points describe the ideal candidate. None of us matched all of these at once when we first joined Anduril. We encourage you to apply even if you believe you meet only part of our wish list.

NICE TO HAVE -You've built or invented something: an app, a website, game, startup -Previous experience working in an engineering setting: a startup (or startup-like environment), engineering school, etc. If you've succeeded in a low structure, high autonomy environment you'll succeed here! -Professional software development lifecycle experience using tools such as version control, CICD systems, etc. -A deep, demonstrated understanding of how computers and networks work, from a single desktop to a multi-cluster cloud node -Experience building scalable backend software systems with various data storage and processing requirements -Experience with industry standard cloud platforms (AWS, Azure), CI/CD tools, and software infrastructure fundamentals (networking, security, distributed systems) -Ability to quickly understand and navigate complex systems and established code bases -Experience implementing robot or autonomous vehicle testing frameworks in a software-in-the-loop or hardware-in-the-loop (HITL) environment -Experience with modern build and deployment tooling (e.g. NixOS, Terraform) -Experience designing complex software systems, and iterating upon designs via a technical design review process -Familiarity with industry standard monitoring, logging, and data management tools and best practices -A bias towards rapid delivery and iteration

Redmond, Washington, United States

Overview Are you interested in developing and optimizing deep learning systems? Are you interested in designing novel technology to accelerate their training and serving for cutting edge models and applications? Do you want to scale large Artificial Intelligence models to their limits on massive supercomputers? Are you interested in being part of an exciting open-source library for deep learning systems? The DeepSpeed team is hiring!

Microsoft's DeepSpeed is an open-source library built on the PyTorch (machine learning framework) ecosystem that combines numerous research innovations and technology advancements to make deep learning efficient and easier to use. DeepSpeed can parallelize across thousands of GPUs and train models with trillions of parameters. Our OSS (Open Source Software) has powered many advanced models like MT-530B and BLOOM, and it supports unprecedented scale and speed for both training and inference.

The DeepSpeed team is also part of the larger Microsoft AI at Scale initiative, which is pioneering the next-generation AI capabilities that are scaled across the company’s products and AI platforms.

The DeepSpeed team is looking for a Senior Researcher in Redmond, WA with passion for innovations and for building high-quality systems that will make significant impact inside and outside of Microsoft. Our team is highly collaborative, innovative, and end-user obsessed. We are looking for candidates with systems skills and passionate about driving innovations to improve the efficiency and effectiveness of deep learning systems. We value creativity, agility, accountability, and a desire to learn new technologies.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities Excels in one or more subareas and gains expertise in a broad area of research. Identifies and articulates problems in an area of research that are academically novel and may directly or indirectly impact business opportunities. Collaborates with other relevant researchers or research groups to contribute to or advance a research agenda. Researches and develops an understanding of the state-of-the-art insights, tools, technologies, or methods being used in the research community. Expands collaborative relationships with relevant product and business groups inside or outside of Microsoft and provides expertise or technology to them.

Location Niskayuna, NY

Description Job Description Summary At GE Aerospace Research, our team develops advanced embedded systems technology for the future of flight. Our technology will enable sustainable air travel and next generation aviation systems for use in commercial as well as military applications. As a Lead Embedded Software Engineer, you will architect and develop state-of-the-art embedded systems for real-time controls and communication applications. You will lead and contribute to advanced research and development programs for GE Aerospace as well as with U.S. Government Agencies. You will collaborate with fellow researchers from a range of technology disciplines, contributing to projects across the breadth of GE Aerospace programs. Job Description Essential Responsibilities: As a Lead Embedded Software Engineer, you will:

Work independently as well as with a team to develop and apply advanced software technologies for embedded controls and communication systems for GE Aerospace products Interact with hardware suppliers and engineering tool providers to identify the best solutions for the most challenging applications Lead small to medium-sized projects or tasks Be responsible for documenting technology and results through patent applications, technical reports, and publications Expand your expertise staying current with advances in embedded software to seek out new ideas and applications Collaborate in a team environment with colleagues across GE Aerospace and government agencies

Qualifications/Requirements:

Bachelor’s degree in Electrical Engineering, Computer Science, or related disciplines with a minimum of 7 years of industry experience OR a master’s degree in Electrical Engineering, Computer Science, or related disciplines with a minimum of 5 years of industry experience OR a Ph.D. in Electrical Engineering, Computer Science, or related disciplines with a minimum of 3 years of industry experience. Strong background in software development for embedded systems (e.g., x86, ARM) Strong embedded programming skills such as: C/C++, Python, and Rust Familiarity with CNSA and NIST cryptographic algorithms Willingness to travel at a minimum of 2 weeks per year Ability to obtain and maintain US Government Security Clearance US Citizenship required Must be willing to work out of an office located in Niskayuna, NY You must submit your application for employment on the careers page at www.gecareers.com to be considered Ideal Candidate Characteristics:

Coding experience with Bash, Python, C#, MATLAB, ARMv8 assembly, RISCV assembly Experience with embedded devices from Intel, AMD, Xilinx, NXP, etc. Experience with hardware-based security (e.g., UEFI, TPM, ARM TrustZone, Secure Boot) Understanding of embedded system security requirements and security techniques Experience with Linux OS and Linux security Experience with OpenSSL and/or wolfSSL Experience with wired and wireless networking protocols or network security Knowledge of 802.1, 802.3, and/or 802.11 standards Experience in software defined networks (SDN) and relevant software such as OpenFlow, Open vSwitch, or Mininet Hands-on experience with embedded hardware (such as protoboards) or networking equipment (such as switches and analyzers) in a laboratory setting Experience with embedded development in an RTOS environment (e.g., VxWorks, FreeRTOS) Demonstrated ability to take an innovative idea from a concept to a product Experience with the Agile methodology of program management The base pay range for this position is 90,000 - 175,000 USD Annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary. This posting is expected to close on June 16, 2024

Location Multiple Locations

Description The Qualcomm Cloud Computing team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive market. Qualcomm’s Cloud AI 100 accelerators are currently deployed at AWS / Cirrascale Cloud and at several large organizations. We are rapidly expanding our ML hardware and software solutions for large scale deployments and are hiring across many disciplines.

We are seeing to hire for multiple machine learning positions in the Qualcomm Cloud team. In this role, you will work with Qualcomm's partners to develop and deploy best in class ML applications (CV, NLP, GenAI, LLMs etc) based on popular frameworks such as PyTorch, TensorFlow and ONNX, that are optimized for Qualcomm's Cloud AI accelerators. The work will include model assessment of throughput, latency and accuracy, model profiling and optimization, end-to-end application pipeline development, integration with customer frameworks and libraries and responsibility for customer documentation, training, and demos. This candidate must possess excellent communication, leadership, interpersonal and organizational skills, and analytical skills.

This role will interact with individuals of all levels and requires an experienced, dedicated professional to effectively collaborate with internal and external stakeholders. The ideal candidate has either developed or deployed deep learning models on popular ML frameworks. If you have a strong appetite for technology and enjoy working in small, agile, empowered teams solving complex problems within a high energy, oftentimes chaotic environment then this is the role for you.

Minimum Qualifications: • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Applications Engineering, Software Development experience, or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Applications Engineering, Software Development experience, or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Applications Engineering, Software Development experience, or related work experience.

• 2+ years of experience with Programming Language such as C, C++, Java, Python, etc. • 1+ year of experience with debugging techniques.Key Responsibilities: Key contributor to Qualcomm’s Cloud AI GitHub repo and developer documentation. Work with developers in large organizations to Onboard them on Qualcomm’s Cloud AI ML stack improve and optimize their Deep Learning models on Qualcomm AI 100 deploy their applications at scale Collaborate and interact with internal teams to analyze and optimize training and inference for deep learning. Work on Triton, ExecuTorch, Inductor, TorchDynamo to build abstraction layers for inference accelerator. Optimize LLM/GenAI workloads for both scale-up (multi-SoC) and scale-out (multi-card) systems. Partner with product management, hardware/software engineering to highlight customer progress, gaps in product features etc.

Redmond, Washington, United States

Overview The Azure AI Platform (AIP) provides organizations across the world with the tooling and infrastructure needed to build and host AI workloads. The AI Platform organization is scaling rapidly, and we are establishing a world-class data analytics platform to support data-driven decision making through the organization.

We are looking to hire a Senior Data Scientist to join the newly formed AI Platform Analytics team. This individual will be responsible for collaborating with teams across AI Platform to establish trustworthy data sets and provide actionable insights and analysis.

We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities

Apply your knowledge in quantitative analysis, data mining, and the presentation of data to inform decision-making. Build data manipulation, processing, and data visualization tools and share these tools and your knowledge across the team, Cloud and AI, and Microsoft. Handle large amounts of data using various tools, including your own. Ensure high-quality and reliable data. Drive end-to-end projects by utilizing, applying and analyzing data to associated business problems. Engage with Upper Level Management by making key business decisions. Mentor other team members. Contribute to data-driven culture by collaborating with product and engineering teams across Azure to establish and share best practices Embody our culture and values

A postdoctoral position is available in Harvard Ophthalmology Artificial Intelligence (AI) Lab (https://ophai.hms.harvard.edu) under the supervision of Dr. Mengyu Wang (https://ophai.hms.harvard.edu/team/dr-wang/) at Schepens Eye Research Institute of Massachusetts Eye and Ear and Harvard Medical School. The start date is flexible, with a preference for candidates capable of starting in August or September 2024. The initial appointment will be for one year with the possibility of extension. Review of applications will begin immediately and will continue until the position is filled. Salary for the postdoctoral fellow will follow the NIH guideline commensurate with years of postdoctoral research experience.

In the course of this interdisciplinary project, the postdoc will collaborate with a team of world-class scientists and clinicians with backgrounds in visual psychophysics, engineering, biostatistics, computer science, and ophthalmology. The postdoc will work on developing statistical and machine learning models to improve the diagnosis and prognosis of common eye diseases such as glaucoma, age-related macular degeneration, and diabetic retinopathy. The postdoc will have access to abundant resources for education, career development and research both from the Harvard hospital campus and Harvard University campus. More than half of our postdocs secured a faculty position after their time in our lab.

For our data resources, we have about 3 million 2D fundus photos and more than 1 million 3D optical coherence tomography scans. Please check http://ophai.hms.harvard.edu/data for more details. For our GPU resources, we have 22 in-house GPUs in total including 8 80-GB Nvidia H100 GPUs, 10 48-GB Nvidia RTX A6000 GPUs, and 4 Nvidia RTX 6000 GPUs. Please check http://ophai.hms.harvard.edu/computing for more details. Our recent research has been published in ICCV 2023, ICLR 2024, CVPR 2024, IEEE Transactions on Medical Imaging, and Medical Image Analysis. Please check https://github.com/Harvard-Ophthalmology-AI-Lab for more details.

The successful applicant will:

1. possess or be on track to complete a PhD or MD with background in computer science, mathematics, computational science, statistics, machine learning, deep learning, computer vision, image processing, biomedical engineering, bioinformatics, visual science and ophthalmology or a related field. Fluency in written and spoken English is essential.

2. have strong programming skills (Python, R, MATLAB, C++, etc.) and in-depth understanding of statistics and machine learning. Experience with Linux clusters is a plus.

3. have a strong and productive publication record.

4. have a strong work ethic and time management skills along with the ability to work independently and within a multidisciplinary team as required.

Your application should include:

1. curriculum vitae

2. statement of past research accomplishments, career goal and how this position will help you achieve your goals

3. Two representative publications

4. contact information for three references

The application should be sent to Mengyu Wang via email (mengyu_wang at meei.harvard.edu) with subject “Postdoctoral Application in Harvard Ophthalmology AI Lab".

Vancouver

Who we are Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly. Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale

We are seeking an experienced researcher to be a founding member of our Vancouver team! We are prioritising someone with experience leading projects in AI applied to autonomous driving or similar robotics or decision-making domains, inclusive, but not limited to the following specific areas: Foundation models for robotics or embodied AI Model-free and model-based reinforcement learning Offline reinforcement learning Large language models Planning with learned models, model predictive control and tree search Imitation learning, inverse reinforcement learning and causal inference Learned agent models: behavioural, oral and physical models of cars, people, and other dynamic agents

Challenges you will own You'll be working on some of the world's hardest problems, and able to attack them in new ways. You'll be a technical leader within our diverse, cross-disciplinary team, helping teach our robots how to drive safely and comfortably in complex real-world environments. This encompasses many aspects of research across perception, prediction, planning, and control, including:

Actively contributing to the Science’s technical leadership community, inclusive of proposing new projects, organising their work, and delivering substantial impact across Wayve. Leveraging our large, rich, and diverse sources of real-world driving data Architecting our models to best employ the latest advances in foundation models, transformers, world models, etc, evaluating and incorporating state-of-the-art techniques into our workflows Investigating learning algorithms to use (e.g. reinforcement learning, behavioural cloning) Leveraging simulation for controlled experimental insight, training data augmentation, and re-simulation Scaling models efficiently across data, model size, and compute, while maintaining efficient deployment on the car Collaborating with cross-functional, international teams to integrate research findings into scalable, production-level solutions Potentially contributing to academic publications for top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc. working in a world-class team, contributing to the scientific community and establishing Wayve as a leader in the field

What you will bring to Wayve Proven track record of research in one or more of the topics above demonstrated through deployed applications or publications. Experience leading a research agenda aligned with larger organisation or company goals Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch, numpy, pandas, etc. Experience bringing a machine learning research concept through the full ML development cycle Excellent problem-solving skills and the ability to work independently as well as in a team environment. Demonstrated ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment. Experience bringing an ML research concept through to production and at scale PhD in Computer Science, Computer Engineering, or a related field

What we offer you The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact

The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.

Location New York, NY Seattle, WA Boston, MA

Description Climate Pledge Friendly helps customers discover and shop for products that are more sustainable. We partner with trusted sustainability certifications to highlight products that meet strict standards and help preserve the natural world. By shifting customer demand towards more sustainable products, we incentivize selling partners to build better selection, creating a virtuous cycle that yields significant environmental benefit at scale.

We are seeking a Senior Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. You will take the lead in conceptualizing, building, and launching models that significantly improve our shopping experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology.

You will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed ML models and services. The types of initiatives you can expect to work on include a) personalized recommendations that help our customers find the right sustainable products on each shopping journey, b) automated solutions that combine ML/LLM and data mining to identify products that align with our sustainability goals and resonate with our customers' values, and c) models to measure the environmental and econometric impacts of sustainable shopping.