<p>We’re reinventing personal transportation — making the future safer, cleaner, and more enjoyable for everyone.</p><p><br></p>

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Zoox is seeking a Senior/Staff Software Engineer, ML Performance Optimization to lead our initiatives and make our Training and Inference platform that enables autonomous driving as fast and efficient as possible. You will work across all ML teams within Zoox and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. You will develop and execute a strategic vision for the ML Performance Optimization team, lead the design, implementation, and operation of cutting-edge ML Training and inference performance optimization techniques, collaborate with cross-functional teams to define requirements and align on architectural decisions, and enable engineers to grow their careers by providing technical guidance and mentorship.

Systems Engineer - Functional Safety

<div class="section page-centered" data-qa="job-description"><div>Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible.&nbsp;</div><div><br></div><div><b>The Opportunity</b></div><div>Are you excited to lead our ML Performance Optimization initiatives and make our Training and Inference platform that enables autonomous driving as fast and efficient as possible? You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and Advanced Hardware Engineering group and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.</div><div><br></div><div>We build and operate the base layer of ML tools, deep learning frameworks, and inference systems used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and act as a force multiplier for our internal customers. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look <a rel="noopener noreferrer" class="postings-link" href="https://zoox.com/autonomy/">here</a>.</div></div><div class="section page-centered"><div><h3>In this role, you will:</h3><ul class="posting-requirements plain-list"><ul><li>Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience.&nbsp;</li><li>Lead the design, implementation, and operation of cutting-edge ML Training and inference performance optimization techniques.</li><li>Collaborate closely with x-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.</li><li>Enable the engineers in the team to grow their careers by providing technical guidance and mentorship.</li></ul></ul></div></div><div class="section page-centered"><div><h3>Qualifications</h3><ul class="posting-requirements plain-list"><ul><li>Strong experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.</li><li>Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.</li><li>Experience using profiling tools like NVIDIA's Nsight or PyTorch's Profiler for identifying model training and serving bottlenecks.</li><li>Proficient in Python and C++</li><li>Experience with model compression techniques to reduce model size and improve performance.</li></ul></ul></div></div><div class="section page-centered" data-qa="closing-description"><div><b>Compensation</b></div><div>There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary range for this position is $200,000 to $332,000. A sign-on bonus may be offered as part of the compensation package. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.</div><div>&nbsp;</div><div>Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.</div><div><br></div><div><b>About Zoox</b></div><div>Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.</div><div><br></div><div><a class="postings-link" href="https://www.linkedin.com/company/zoox-inc">Follow us on LinkedIn</a></div><div><br></div><div><b>Accommodations</b></div><div>If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.</div><div><br></div><div><i><b>A Final Note:</b></i></div><div><i>You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.</i></div></div>

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The AI/ML driven ASIC Design and Implementation Automation Expert will explore methodologies, flows, and tools to improve efficiency and quality for SoC and IP development. They will work with AI/ML and automation experts, develop prototype solutions, and pilot automation on actual designs within the Advanced Chip Engineering (ACE) organization. The role involves collaborating with various engineering teams to drive digital transformation using state-of-the-art AI/ML techniques for automotive processors and advanced microcontrollers, enabling automated building of complex SoCs.

NXP Semiconductors N.V. (NASDAQ: NXPI) enables a smarter, safer, and more sustainable world through innovation. As the world leader in secure connectivity solutions for embedded applications, NXP is pushing boundaries in the automotive, industrial & IoT, mobile, and communication infrastructure markets. For more information, visit www.nxp.comRead MoreCareer Development OpportunitiesBright Minds. Bright Futures.We believe that a key component to growing our business is to develop our people. To enable you to grow your career at NXP, we offer online and offline learning opportunities to help you develop some of your core and professional skills.Read MoreCommitment At NXP.We recognize NXP is a powerful change agent as we continue to deliver innovative solutions that advance a more sustainable future.

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<p>As an “<b>AI/ML driven ASIC Design and Implementation Automation Expert</b>” in our Advanced Chip Engineering (ACE) organization, you will work in a dynamic environment to explore methodology, flows and tools to improve efficiency and quality of results (power, performance, area, and quality) for SoC and IP development teams across the organization. You'll be working and connecting with AI/ML and automation experts in the industry as well as academia to explore state-of-the-art AI/ML CAD techniques as a part of VLSI CAD SW, prescribe key methods and requirements for tools &amp; features to leverage for ASIC design.</p><p><br>In this role, you will develop prototype solutions to evaluate various state-of-the-art AI/ML techniques to identify the best solutions for NXP designs. While exploring these new ways of working, successful candidates will be working on actual designs and implementation to pilot and develop the automation.</p><p><br>This opportunity is within ACE 'Design Methodologies and Automation' organization to enable Digital Transformation to leverage state-of-the-art AI/ML ideas to improve NXP designs for the Automotive Processors and Advanced microcontrollers in NXP.<br>The right candidate will be working in a fast-paced engineering environment, on a leading-edge advanced node technologies enabling automated building of exciting and complex SoCs.<br>&nbsp;</p><p><b>Job Summary</b>:</p><ul><li>Explore research ideas and solutions that bring AI/ML applications to VLSI design</li><li>Work closely with Academic research communities in AI/ML for VLSI design, Architecture teams, IP and SoC designers and SoC Implementation teams from multiple sites to explore and evaluate for leading edge SoC technologies serving multiple industries</li><li>These automation applications include use of GenAI, Reinforcement Learning, Graph Neural Networks, and convolutional Networks</li><li>Strong AI/ML expertise, software and CAD background required</li></ul><p></p><p><b>Cross functional aspects</b>:</p><ul><li>In this role, the candidate will work with multiple NXP Engineering teams, including Architecture, IP &amp; SoC design, verification and implementation functions, coordinate and drive groundbreaking initiatives for Digital Transformation.<br>&nbsp;</li></ul><p><b>Qualifications</b>:</p><ul><li>BS or MS in Computer Science, Electrical Engineering, Computer Engineering or related disciplines with strong background in SW development</li><li>Hands-on expertise in programming using Python/C++</li><li>5+ years of experience in AI and ML techniques (LLMs, CNN, RNN, and GraphNN) with experience of application to real world optimization problems</li><li>Data structures, algorithms, and SW development for optimization problems</li><li>Hands on experience in Unix/Linux, revision control (Git, BitBucket), SW development and debug tools</li><li>Excellent analytical problem-solving skills</li><li>Strong verbal and written communication skills</li></ul><p></p><p><b>Desirable skills/experience:</b></p><ul><li>Strong understanding of design, layout, constraints (SDC, Clocks, CDC, RDC), Static timing analysis, Low-power, and Power-aware flows (UPF)</li><li>Prior experience in VLSI CAD methodology and tool development</li><li>Good understanding of HDL: System Verilog, Verilog, VHDL, front-end design, physical design and layout <span style="overflow-wrap: break-word; display: inline; text-decoration: inherit; hyphens: auto;">implementation/generation</span> flows and tools</li><li>Understanding or prior experience with EDA tools for design, verification, DFT and implementation</li><li>Experience with Design revision control (GIT, DesignSync) and Make</li><li>Splunk, Jenkins, LSF and CI/CD process</li></ul><p></p><p><b>Job location: </b></p><ul><li>San Diego, CA</li></ul><p></p><p><a href="https://www.nxp.com/company/about-nxp/worldwide-locations/united-states:USA" target="_blank" rel="noopener noreferrer">More information about NXP in the United States...</a></p><p></p><p>NXP is an Equal <span><span style="overflow-wrap: break-word; display: inline; text-decoration: inherit; hyphens: auto;">Opportunity/Affirmative</span></span> Action Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, NXP will provide reasonable accommodations for otherwise qualified disabled individuals.</p><p></p>#LI-6692

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This assessment gives us an idea of your C++ skills- Companies that evaluate this skillset in interviews: Rockstar Games, Ubisoft, Mayhem Studios, etc.- 10 Multiple Choice questions- Average time to complete: 7 to 10 minutes

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