The Autonomy Software Metrics team is responsible for providing engineers and leadership at Zoox with tools to evaluate the behavior of Zoox’s autonomy stack using simulation. The team collaborates with experts across the organization to ensure a high safety bar, great customer experience, and rapid feedback to developers. The metrics team is responsible for evaluating the complete end-to-end customer experience through simulation, evaluating factors that impact safety, comfort, legality, road citizenship, progress, and more. You’ll be part of a passionate team making transportation safer, smarter, and more sustainable. This role gives you high visibility within the company and is critical for successfully launching our autonomous driving software.

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 Seattle, WA New York, NY

Description We are looking for an Applied Scientist to join our Seattle team. As an Applied Scientist, you are able to use a range of science methodologies to solve challenging business problems when the solution is unclear. Our team solves a broad range of problems ranging from natural knowledge understanding of third-party shoppable content, product and content recommendation to social media influencers and their audiences, determining optimal compensation for creators, and mitigating fraud. We generate deep semantic understanding of the photos, and videos in shoppable content created by our creators for efficient processing and appropriate placements for the best customer experience. For example, you may lead the development of reinforcement learning models such as MAB to rank content/product to be shown to influencers. To achieve this, a deep understanding of the quality and relevance of content must be established through ML models that provide those contexts for ranking.

In order to be successful in our team, you need a combination of business acumen, broad knowledge of statistics, deep understanding of ML algorithms, and an analytical mindset. You thrive in a collaborative environment, and are passionate about learning. Our team utilizes a variety of AWS tools such as SageMaker, S3, and EC2 with a variety of skillset in shallow and deep learning ML models, particularly in NLP and CV. You will bring knowledge in many of these domains along with your own specialties.

Redmond, Washington, United States

Overview The Microsoft Research AI Frontiers group in Redmond is looking for a Senior Research Software Engineer to build state-of-the-art tools for evaluating and understanding foundation models, with a focus of real-world uses of Artificial Intelligence (AI). Our team conducts influential research published at top-tier venues in AI and ML (including NeurIPS, ICML, AAAI, and FAccT) and works within Microsoft’s Responsible AI ecosystem to impact our AI-driven technologies such as Azure, Office, and Bing.

We are seeking candidates with demonstrated ability for technical work in the space of large foundational models with proficient coding and machine learning skills. The preferred candidate is:

Passionate about rigorous evaluation, understanding, and development of foundational models.
Motivated to make successful research methods accessible to the AI community through prototypes, open-source libraries, and development tools. Proficient in design thinking and Object Oriented Design (OOD), building clean, modular, maintainable and user-friendly open-source ML Experienced in measuring and maximizing the impact of open-source libraries.

As a Senior Research Software Engineer, you will play a crucial role in designing and developing impactful, high quality and well-engineered frameworks to empower the scientific evaluation, understanding, and development of foundational models. You will work closely with a team of passionate researchers and engineers to make sure such frameworks are compatible with modern cloud platforms, Machine Learning (ML) frameworks and libraries, model architectures, and various data modalities. You will also play a central role in defining and running large-scale experiments that contribute to our team’s research.

We are looking for a team player interested in developing next-generation platforms and tools for Machine Learning (ML) as well as conducting state-of-the-art research. Topics of interest include but are not limited to rigorous evaluation and benchmarking, advances in AI interpretability, bias and fairness, and safety in real-world deployments. Our group takes a holistic approach to studying foundational models that includes a variety of data modalities (language, vision, multi-modal, and structured data) and modern model architectures. Candidates should demonstrate expertise in many of these aspects or show that they are interested in generalizing their skills into a variety of modalities and architectures.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

Responsibilities Collaborate with a dedicated research and engineering team to design and develop ML frameworks for model evaluation and understanding.

• Define benchmarks and execute experiments for rigorous model evaluation and understanding.

• System Design and Object-Oriented Design: Envision elegant solutions and craft scalable and efficient systems to drive the success of our Machile Learning (ML) frameworks. Develop clean, modular, and maintainable code to shape the foundation of our evaluation framework.

• Work closely with partner engineering teams in both research and production.

• Mentor or onboard incoming engineering contributors and empower them to maximize the team’s impact.

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.

Location Seattle, WA Palo Alto, CA

Description Amazon’s product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on an AI-first initiative to continue to improve the way we do search through the use of large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced multi-modal deep-learning models on very large scale datasets, specifically through the use of advanced systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge Computer Vision and Deep Learning technologies and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: * How can multi-modal inputs in deep-learning models help us deliver delightful shopping experiences to millions of Amazon customers? * Can combining multi-modal data and very large scale deep-learning models help us provide a step-function improvement to the overall model understanding and reasoning capabilities? We are looking for exceptional scientists who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization.

Figma is growing our team of passionate people on a mission to make design accessible to all. Born on the Web, Figma helps entire product teams brainstorm, design and build better products — from start to finish. Whether it’s consolidating tools, simplifying workflows, or collaborating across teams and time zones, Figma makes the design process faster, more efficient, and fun while keeping everyone on the same page. From great products to long-lasting companies, we believe that nothing great is made alone—come make with us!

We’re looking for engineers with a Machine Learning and Artificial Intelligence background to improve our products and build new capabilities. You will be driving fundamental and applied research in this area. You will be combining industry best practices and a first-principles approach to design and build ML models that will improve Figma’s design and collaboration tool.

What you’ll do at Figma:

• You will be driving fundamental and applied research in ML/AI. You will explore the boundaries of what is possible with the current technology set.
• You will be combining industry best practices and a first-principles approach to design and build ML models.
• Work in concert with product and infrastructure engineers to improve Figma’s design and collaboration tool through ML powered product features.
• We'd love to hear from you if you have:
• 5+ years of experience in programming languages (Python, C++, Java or R)
• 3+ years of experience in one or more of the following areas: machine learning, natural language processing/understanding, computer vision, generative models.
• Proven experience researching, building and/or fine-tuning ML models in production environments
• Experience communicating and working across functions to drive solutions

While not required, It’s an added plus if you also have:

• Proven track record of planning multi-year roadmap in which shorter-term projects ladder to the long-term vision.
• Experience in mentoring/influencing senior engineers across organizations.

About the role 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.

Location: Sunnyvale, California, USA

Are you a gamer? Are you passionate about the cutting edge of foundation models and Multiodal LLM Agent for 3D world creation for future gaming?

Cybever.ai is on the lookout for an innovative AI Research Scientist to join our dynamic team and revolutionize the world of generative AI for 3D content.

What You'll Be Doing:

• Research and Development: Lead groundbreaking research in multimodal large language models (LLMs) and AI agents.
• 3D Content Creation: Develop advanced models and algorithms to create large-scale 3D assets and environments from text or images, enhancing our AI-powered creative suite.
• Collaboration and Integration: Work closely with the engineering team to integrate new AI capabilities into our existing products, ensuring they meet the needs of game developers, movie productions, and 3D artists.
• Innovation in AI: Stay ahead of the curve by publishing research, attending conferences, participating in open source projects, and collaborating with the global AI research community.

You're Probably a Match If You Have:

• Strong Research Background: Ph.D. or equivalent experience in AI, machine learning, computer vision, computer graphics, or related fields.
• Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or similar frameworks.
• 3D Software Experience: Hands-on experience with tools like Blender, Houdini, Unreal Engine, or Unity, or a willingness to learn.
• Relevant Experience: Demonstrated work in computer vision or computer graphics, with a portfolio of projects or publications to showcase your expertise.

About Cybever:

Cybever, headquartered in the heart of Silicon Valley and founded by ex-Googlers, is a pioneer in the generative AI space, transforming how game developers and artists create 3D content. Our innovative tools enable creating large-scale, high-fidelity, and interactive 3D environments in minutes, freeing up creators to focus on what they do best. With partnerships with industry leaders like Unreal Engine, we are at the forefront of integrating AI into the creative process, empowering developers worldwide to realize their visions easier and faster.

Employment Type:

• Full-Time Employment: This is a full-time position with potential for H1B and OPT sponsorship.
• International Opportunities: We are also open to hiring international contractors who meet our qualifications.
• Research Intern or Residency: Ideal for graduate students, this is a part-time or full-time opportunity to gain hands-on research experience while completing your studies.

Join us at Cybever and be a part of a team that's shaping the future of 3D creation. If you're ready to push the boundaries of what's possible with AI, we want to hear from you!

The Perception team at Zoox is responsible for developing the eyes and ears of our self driving car. Navigating safely and competently in the world requires us to detect, classify, track and understand several different attributes of all the objects around us that we might interact with, all in real time and with very high precision.

As a member of the Perception team at Zoox, you will be responsible for developing and improving state of the art machine learning techniques for doing everything from 2D/3D object detection, panoptic segmentation, tracking, to attribute classification. You will be working not just with our team of talented engineers and researchers in perception, but cross functionally with several teams including sensors, prediction and planning, and you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms.

Location Sunnyvale, CA

Description Are you fueled by a passion for computer vision, machine learning and AI, and are eager to leverage your skills to enrich the lives of millions across the globe? Join us at Ring AI team, where we're not just offering a job, but an opportunity to revolutionize safety and convenience in our neighborhoods through cutting-edge innovation.

You will be part of a dynamic team dedicated to pushing the boundaries of computer vision, machine learning and AI to deliver an unparalleled user experience for our neighbors. This position presents an exceptional opportunity for you to pioneer and innovate in AI, making a profound impact on millions of customers worldwide. You will partner with world-class AI scientists, engineers, product managers and other experts to develop industry-leading AI algorithms and systems for a diverse array of Ring and Blink products, enhancing the lives of millions of customers globally. Join us in shaping the future of AI innovation at Ring and Blink, where exciting challenges await!

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 the MLE, you will collaborate with researchers to perform research operations using existing infrastructure. You will use your judgment in complex scenarios and help apply standard techniques to various technical problems. Specifically, you will:

• Characterize neural network quality, failure modes, and edge cases based on research data
• Maintain awareness of current trends in relevant areas of research and technology
• Coordinate with researchers and accurately convey the status of experiments
• Manage a large number of concurrent experiments and make accurate time estimates for deadlines
• Review experimental results and suggest theoretical or process improvements for future iterations
• Write technical reports indicating qualitative and quantitative results to external parties

※Location※ South Korea Seoul / Pangyo

※Description※ 1) Deep learning compression and optimization - Development of algorithms for compression and optimization of deep learning networks - Perform deep learning network embedding (requires understanding of HW platform)

2) AD vision recognition SW - Development of deep learning recognition technology based on sensors such as cameras - Development of pre- and post-processing algorithms and function output - Development of optimization of image recognition algorithm

3) AD decision/control SW - Development of information-based map generation technology recognized by many vehicles - Development of learning-based nearby object behavior prediction model - Development of driving mode determination and collision prevention function of Lv 3 autonomous driving system

Location San Diego

Description

Artificial Intelligence is changing the world for the benefit of human beings and societies. QUALCOMM, as the world's leading mobile computing platform provider, is committed to enable the wide deployment of intelligent solutions on all possible devices – like smart phones, autonomous vehicles, robotics and IOT devices. Qualcomm is creating building blocks for the intelligent edge.

We are part of Qualcomm AI Research, and we focus on advancing Edge AI machine learning technology – including model fine tuning, hardware acceleration, model quantization, model compression, network architecture search (NAS), edge inference and related fields. Come join us on this exciting journey. In this particular role, you will work in a dynamic research environment, be part of a multi-disciplinary team of researchers and software engineers who work with cutting edge AI frameworks and tools. You will architect, design, develop, test, and deploy on- and off-device benchmarking workflows for model zoos.

Minimum Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.The successful applicant should have a strong theoretical background and proven hands-on experience with AI as modern software-, web-, and cloud-engineering.

Must have experience and skills: Strong theoretical background in AI and general ML techniques Proven hands-on experience with model training, inference, and evaluation. Proven hands-on experience with PyTorch, ONNX, TensorFlow, CUDA, and others. Experience developing data pipelines for ML/AI training and inferencing in the cloud. Prior experience in deploying containerized (web-) applications to IAAS environments such as AWS (preferred), Azure or GCP, backed by Dev-Ops and CI/CD technologies. Strong Linux command line skills. Strong experience with Docker and Git. Strong general analytical and debugging skills. Prior experience working in agile environments. Prior experience in collaborating with multi-disciplinary teams across time zones. Strong team player, communicator, presenter, mentor, and teacher. Preferred extra experience and skills: Prior experience with model quantization, profiling and running models on edge devices. Prior experience in developing full stack web applications using frameworks such as Ruby-on-Rails (preferred), Django, Phoenix/Elixir, Spring, Node.js or others. Knowledge of relational database design and optimization, hands on experience with running Postgres (preferred), MySQL or other relational databases in production Preferred qualifications: Bachelor's, Master's and/or PhD degree in Computer Science, Engineering, Information Systems, or related field and 2-5 years of work experience in Software Engineering, Systems Engineering, Hardware Engineering or related.

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