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

Redwood City, CA; or Remote, US

We help make autonomous technologies more efficient, safer, and accessible.

Helm.ai builds AI software for autonomous driving and robotics. Our "Deep Teaching" methodology is uniquely data and capital efficient, allowing us to surpass traditional approaches. Our unsupervised learning software can train neural networks without the need for human annotation or simulation and is hardware-agnostic. We work with some of the world's largest automotive manufacturers and we've raised over $100M from Honda, Goodyear Ventures, Mando, and others to help us scale.

Our team is made up of people with a diverse set of experiences in software and academia. We work together towards one common goal: to integrate the software you'll help us build into hundreds of millions of vehicles.

We offer: - Competitive health insurance options - 401K plan management - Remote-friendly and flexible team culture - Free lunch and fully-stocked kitchen in our South Bay office - Additional perks: monthly wellness stipend, office set up allowance, company retreats, and more to come as we scale - The opportunity to work on one of the most interesting, impactful problems of the decade

Visit our website to apply for a position.

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.

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

Redmond, Washington, United States

Overview In Mixed Reality, people—not devices—are at the center of everything we do. Our tech moves beyond screens and pixels, creating a new reality aimed at bringing us closer together—whether that’s scientists “meeting” on the surface of a virtual Mars or some yet undreamt-of possibility. To get there, we’re incorporating diverse groundbreaking technologies, from the revolutionary Holographic Processing Unit to computer vision, machine learning, human-computer interaction, and more. We’re a growing team of talented engineers and artists putting technology on a human path across all Windows devices, including Microsoft HoloLens, the Internet of Things, phones, tablets, desktops, and Xbox. We believe there is a better way. If you do too, we need you! 

You are drawn to work on the latest and most innovative products in the world. You seek projects that will transform how people interact with technology. You have a drive to grow your skillset by finding unique challenges that have yet to be solved. We are looking for Senior Software Engineer to come and join us in delivering the next wave of holographic experiences in an exciting new project. 

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 Incorporate the latest Artificial Intelligence, Machine Learning, Computer Vision and Sensor Fusion capabilities into the design of our Products and Services Characterize various sensors like inertial measurement units, magnetometers, visual light cameras, depth cameras, GPS etc. to understand their properties and how they relate to the accuracy of tracking, mapping, and localization. Implement and design innovative measurement solutions to quantify the accuracy and reliability of Mixed Reality devices against industry gold standard ground-truth systems Partner with engineers, designers, and program managers to deliver solid technical designs. Embody our Culture and Values

Location San Diego

Description

Qualcomm AI Research is looking for world-class algorithm engineers in general domain machine learning, especially deep learning, generative AI, LLM, LVM. Come join a high-caliber team of engineers building advanced machine learning technology, best-in-class solutions, and user friendly model optimization tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet) to enable state-of-the-art networks to run on devices with limited power, memory, and computation.

Members of our team enjoy the opportunity to participate in cutting edge research while simultaneously contributing technology that will be deployed worldwide in our industry-leading devices. You will be part of a multi-disciplinary talented team working on on-device generative AI optimization. Collaborate in a cross-functional environment spanning hardware, software and systems. See your design in action on industry-leading chips embedded in the next generation of smartphones, autonomous vehicles, robotics, and IOT devices.

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 R&D work responsibility for this position focuses on the following: Algorithms research and development in the area of Generative AI, LVM, LLM, Multi-modality Efficient inference algorithms research and development, e.g. batching, KV caching, efficient attentions, long context, speculative decoding Advanced quantization algorithms research and development for complex generative models, e.g., gradient/non-gradient based optimization, equivalent/non-equivalent transformation, automatic mixed precision, hardware in loop Model compression, lossy or lossless, structural and neural search Optimization based learning and learning based optimization Generative AI system prototyping Apply solutions toward system innovations for model efficiency advancement on device as well as in the cloud Python, Pytorch programmer Preferred Qualifications: Master's degree in Computer Science, Engineering, Information Systems, or related field. PHD's degree is preferred. 2+ years of experience with Machine Learning algorithms or systems engineering or related work experience

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.

Location Sunnyvale, CA Bellevue, WA Seattle, WA

Description The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Science Manager with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems.

As an Applied Science Manager with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision.

Redmond, Washington, United States

Overview We are seeking highly skilled and passionate research scientists to join Responsible & Open Ai Research (ROAR) in Azure Cognitive Services in Redmond, WA.

As a Principal Research Scientist, you will play a key role in advancing Responsible AI approaches to ensure safe releases of GenAI models such as GPT-4o, DALL-E, Sora, and beyond, as well as to expand and enhance the capability of Azure AI Content Safety Service.

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 Conduct cutting-edge, deployment-driven research to develop Responsible AI definitions, methodologies, algorithms, and models for both measurement and mitigation of textual and multimodal AI risks. Stay abreast of the latest advancements in the field and contribute to the scientific community through publications at top venues.

Enable the safe release of multimodal models from OpenAI in Azure OpenAI Service, expand and enhance the Azure AI Content Safety Service with new detection/mitigation technologies in text and multimodal content. Develop innovative approaches to address AI safety challenges for diverse customer scenarios.

Review business and product requirements and incorporate state-of-the-art research to formulate plans that will meet business goals. Identifies gaps and determines which tools, technologies, and methods to incorporate to ensure quality and scientific rigor. Proactively provides mentorship and coaching to less experienced and mid-level team members.

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

Where you will have an impact We are seeking an experienced researcher to be a founding member of our Vancouver team! We are prioritising someone with experience actively participating in AI projects 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 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 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, evaluating and incorporating state-of-the-art techniques into our workflows. 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 Collaborate with cross-functional teams to integrate research findings into scalable, production-level solutions. 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, 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. 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. Desirable: 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 Competitive compensation and benefits 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

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).

※Location※ South Korea, Uiwang

※Description※ 1) AI Perception - RGB image based object/scene reconstruction (Nerf, GS, LRM) - Object detection / analysi - Image-Text multimodal model

2) Manipulation Vision - Development of vision-based Bimanual Manipulation using deep learning technology

3) On-Device AI - Development of lightweight deep learning model and on-device AI optimization technology

4) Mobile robot SLAM- Development of algorithms for Perception, SLAM, Motion control and Path planning

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 Multiple Locations

Description

Qualcomm's Multimedia R&D and Standards Group is seeking candidates for Video Compression Research Engineer positions. You will be part of world-renowned team of video compression experts. The team develops algorithms, hardware architectures, and systems for state-of-the-art applications of classical and machine learning methods in video compression, video processing, point cloud coding and processing, AR/VR and computer vision use cases. The successful candidate for this position will be a highly self-directed individual with strong creative and analytic skills and a passion for video compression technology. You will work on, but not be limited to, developing new applications of classical and machine learning methods in video compression improving state-of-the-art video codecs.

We are considering candidates with various levels of experience. We are flexible on location and open to hiring anywhere, preferred locations are USA, Germany and Taiwan.

Responsibilities: Contribute to the conception, development, implementation, and optimization of new algorithms extending existing techniques and systems allowing improved video compression. Initiate ideas, design and implement algorithms for superior hardware encoder performance, including perceptually based bit allocation. Develop new algorithms for deep learning-based video compression solutions. Represent Qualcomm in the related standardization forums: JVET, MPEG Video, and ITU-T/VCEG. Document and present new algorithms and implementations in various forms, including standards contributions, patent applications, conference and journal publications, presentations, etc. Ideal candidate would have the skills/experience below: Expert knowledge of the theory, algorithms, and techniques used in video and image coding. Knowledge and experience of video codecs and their test models, such as ECM, VVC, HEVC and AV1. Experience with deep learning structures CNN, RNN, autoencoder etc. and frameworks like TensorFlow/PyTorch. Track record of successful research accomplishments demonstrated through published papers, and/or patent applications in the fields of video coding or video processing. Solid programming and debugging skills in C/C++. Strong written and verbal English communication skills, great work ethic, and ability to work in a team environment to accomplish common goals. PhD or Masters degree in Electrical Engineering, Computer Science, Physics, Mathematics or similar field, or equivalent practical experience.

Qualifications: PhD or Masters degree in Electrical Engineering, Computer Science, Physics, Mathematics, or similar fields. 1+ years of experience with programming language such as C, C++, MATLAB, etc.