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CVPR 2024 Career Website

Here we highlight career opportunities submitted by our Exhibitors, and other top industry, academic, and non-profit leaders. We would like to thank each of our exhibitors for supporting CVPR 2024. Opportunities can be sorted by job category, location, and filtered by any other field using the search box. For information on how to post an opportunity, please visit the help page, linked in the navigation bar above.

Search Opportunities

Redmond, Washington, United States


Overview We are seeking a Principal Research Engineer to join our organization and help improve steerability and control Large Language Models (LLMs) and other AI systems. Our team currently develops Guidance, a fully open-source project that enables developers to control language models more precisely and efficiently with constrained decoding.

As a Principal Research Engineer, you will play a crucial role in advancing the frontier of constrained decoding and imagining new application programming interface (APIs) for language models. If you’re excited about links between formal grammars and generative AI, deeply understanding and optimizing LLM inference, enabling more responsible AI without finetuning and RLHF, and/or exploring fundamental changes to the “text-in, text-out” API, we’d love to hear from you. Our team offers a vibrant environment for cutting-edge, multidisciplinary research. We have a long track record of open-source code and open publication policies, and you’ll have the opportunity to collaborate with world-leading experts across Microsoft and top academic institutions across the world.

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 Develop and implement new constrained decoding research techniques for increasing LLM inference quality and/or efficiency. Example areas of interest include speculative execution, new decoding strategies (e.g. extensions to beam search), “classifier in the loop” decoding for responsible AI, improving AI planning, and explorations of attention-masking based constraints. Re-imagine the use and construction of context-free grammars (CFG) and beyond to fit Generative AI. Examples of improvements here include better tools for constructing formal grammars, extensions to Earley parsing, and efficient batch processing for constrained generation. Consideration of how these techniques are presented to developers – who may not be well versed in grammars and constrained generation -- in an intuitive, idiomatic programming syntax is also top of mind. Design principled evaluation frameworks and benchmarks for measuring the effects of constrained decoding on a model. Some areas of interest to study carefully include efficiency (token throughput and latency), generation quality, and impacts of constrained decoding on AI safety. Publish your research in top AI conferences and contribute your research advances to the guidance open-source project. Other

Embody our Culture and Values


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London


Who are we?

Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning, computer vision and reinforcement learning. Leveraging our multi-national world-class team of researchers and engineers, we’re using data to learn more intelligent algorithms to bring autonomy for everyone, everywhere. We aim to be the future of self-driving cars, learning from experience and data.

Where you’ll have an impact

We are currently looking for people with research expertise in AI applied to autonomous driving or similar robotics or decision making domain, inclusive, but not limited to the following specific areas:

Foundation models for robotics 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: behavioral and physical models of cars, people, and other dynamic agents You'll be working on some of the world's hardest problems, and able to attack them in new ways. You'll be a key member of 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:

How to leverage our large, rich, and diverse sources of real-world driving data How to architect our models to best employ the latest advances in foundation models, transformers, world models, etc. Which learning algorithms to use (e.g. reinforcement learning, behavioural cloning) How to leverage simulation for controlled experimental insight, training data augmentation, and re-simulation How to scale models efficiently across data, model size, and compute, while maintaining efficient deployment on the car You also have the potential to contribute to academic publications for top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc. working in a world-class team to achieve this.

What you’ll bring to Wayve

Thorough knowledge of and 5+ years applied experience in AI research, computer vision, deep learning, reinforcement learning or robotics Ability to deliver high quality code and familiarity with deep learning frameworks (Python and Pytorch preferred) Experience leading a research agenda aligned with larger goals Industrial and / or academic experience in deep learning, software engineering, automotive or robotics Experience working with training data, metrics, visualisation tools, and in-depth analysis of results Ability to understand, author and critique cutting-edge research papers Familiarity with code-reviewing, C++, Linux, Git is a plus PhD in a relevant area and / or track records of delivering value through machine learning are a big plus. What we offer you

Attractive compensation with salary and equity Immersion in a team of world-class researchers, engineers and entrepreneurs A unique position to shape the future of autonomy and tackle the biggest challenge of our time Bespoke learning and development opportunities Relocation support with visa sponsorship Flexible working hours - we trust you to do your job well, at times that suit you and your time Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more!


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Vancouver, British Columbia, Canada


Overview Microsoft Research (MSR), a leading industrial research laboratory comprised of over 1,000 computer scientists working across the United States, United Kingdom, China, India, Canada, and the Netherlands.

We are currently seeking  a Researcher in the area of  Artificial Specialized Intelligence located in Vancouver, British Columbia, with a keen interest in developing cutting-edge large foundation models and post-training techniques for different domains and scenarios. This is an opportunity to drive an ambitious research agenda while collaborating with diverse teams to push for novel applications of those areas.  
  Over the past 30 years, our scientists have not only conducted world-class computer science research but also integrated advanced technologies into our products and services, positively impacting millions of lives and propelling Microsoft to the forefront of digital transformation.   Responsibilities Conduct cutting-edge research in large foundation models, focusing on applying large foundation models in specific domain. Collaborate with cross-functional teams to integrate solutions into Artificial Intelligence (AI) -driven system. Develop and maintain research prototypes and software tools, ensuring that they are well-documented and adhere to best practices in software development. Publish research findings in top-tier conferences and journals and present your work at industry events. Collaborate with other AI researchers and engineers, sharing knowledge and expertise to foster a culture of innovation and continuous learning within the team.


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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


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We are seeking a highly motivated candidate for a fully funded PhD position to work in 3D computer graphics and 3D computer vision.

The successful candidate will join the 3D Graphics and Vision research group led by Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College Dublin, Ireland to work on topics related to generative AI in the 3D domain.

The School of Computer Science and Statistics at Trinity College Dublin is a collegiate, friendly, and research-intensive centre for academic study and research excellence. The School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS Subject Rankings 2018, 2019, 2020, 2021).

The PhD student is expected to conduct fundamental research and publish in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV, SIGGRAPH) and journals (TPAMI, IJCV).

The start date of the position is September 01, 2024. The position is fully funded for 4 years by Science Foundation Ireland.

The successful candidate will require the following skills and knowledge: • Bachelor or Master in Computer Science or related fields; • Strong competence in computer graphics, computer vision; • Solid experience in academic research and publications is an advantage; • Additional background in math, statistics, or physics is an advantage. • Hands-on experience in training deep models; • Hands-on experience in computer graphics and computer vision application development such as OpenGL, OpenCV, CUDA, Blender; • Strong programming skills in C++, Python. Capability in implementing systems based on open-source software.

Applicants should provide the following information: • A comprehensive CV; • Academic transcripts of Bachelor and Master’s degree; • The name and contact details of two referees.

Interested candidates can email Binh-Son Hua (https://sonhua.github.io) for an informal discussion of the position. Applications will be reviewed on a rolling basis until the position has been filled.


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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).


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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.

Apply

Vancouver, British Columbia, Canada


Overview Microsoft Research (MSR), a leading industrial research laboratory comprised of over 1,000 computer scientists working across the United States, United Kingdom, China, India, Canada, and the Netherlands.

We are currently seeking a Senior Researcher in the area of  Artificial Specialized Intelligence located in Vancouver, British Columbia, with a keen interest in developing cutting-edge large foundation models and post-training techniques for different domains and scenarios. This is an opportunity to drive an ambitious research agenda while collaborating with diverse teams to push for novel applications of those areas.  
  Over the past 30 years, our scientists have not only conducted world-class computer science research but also integrated advanced technologies into our products and services, positively impacting millions of lives and propelling Microsoft to the forefront of digital transformation.

Responsibilities Conduct cutting-edge research in large foundation models, focusing on applying large foundation models in specific domain. Collaborate with cross-functional teams to integrate solutions into Artificial Intelligence (AI) -driven system. Develop and maintain research prototypes and software tools, ensuring that they are well-documented and adhere to best practices in software development. Publish research findings in top-tier conferences and journals and present your work at industry events. Collaborate with other AI researchers and engineers, sharing knowledge and expertise to foster a culture of innovation and continuous learning within the team.


Apply

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, you will work collaboratively to improve our models and iterate on novel research directions, sometimes in just days. We're looking for talented engineers who would enjoy applying their skills to deeply complex and novel AI problems. Specifically, you will:

  • Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale
  • Carefully execute the development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole
  • Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms

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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.


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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.


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Location Seattle, WA


Description Amazon's Compliance Shared Services (CoSS) is looking for a smart, energetic, and creative Sr Applied Scientist to extend and invent state-of-the-art research in multi-modal architectures, large language models across federated and continuous learning paradigms spread across multiple systems to join the Applied Research Science team in Seattle. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale that increase automation accuracy and coverage, and extend and invent new research as a key author to deliver re-usable foundational capabilities for automation.

You will analyze and process large amounts of image, text and tabular data from product detail pages, combine them with additional external and internal sources of multi-modal data, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms in federated and continuous learning modes that can be integrated and launched across multiple systems. You will partner with engineers and product managers across multiple Amazon teams to design new ML solutions implemented across worldwide Amazon stores for the entire Amazon product catalog.


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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!

The AI Platform team at Figma is working on an exciting mission of expanding the frontiers of AI for creativity, and developing magical experiences in Figma products. This involves making existing features like search smarter, and incorporating new features using cutting edge Generative AI and deep learning techniques. We’re looking for engineers with a background in Machine Learning and Artificial Intelligence 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:

  • Driving fundamental and applied research in ML/AI using Generative AI, deep learning and classical machine learning, with Figma product use cases in mind.
  • Formulate and implement new modeling approaches both to improve the effectiveness of Figma’s current models as well as enable the launch of entirely new AI-powered product features.
  • Work in concert with other ML researchers, as well as product and infrastructure engineers to productionize new models and systems to power features in Figma’s design and collaboration tool.
  • Expand the boundaries of what is possible with the current technology set and experiment with novel ideas.
  • Publish scientific work on problems relevant to Figma in leading conferences like ICML, NeurIPS, CVPR etc.

We'd love to hear from you if you have:

  • Recently obtained or is in the process of obtaining a PhD in AI, Computer Science or a related field. Degree must be completed prior to starting at Figma.
  • Demonstrated expertise in machine learning with a publication record in relevant conferences, or a track record in applying machine learning techniques to products.
  • Experience in Python and machine learning frameworks (such as PyTorch, TensorFlow or JAX).
  • Experience building systems based on deep learning, natural language processing, computer vision, and/or generative models.
  • Experience solving sophisticated problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.
  • Experience communicating and working across functions to drive solutions.

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

  • Experience working in industry on relevant AI projects through internships or past full time work.
  • Publications in recent advances in AI like Large language models (LLMs), Vision language Models (VLMs) or diffusion models.

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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

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