deep learning engineer

Optimal Inc.

<div>Machine Learning Research Engineer (ScientificEngineering AI) 
Urgent Hiring Requirement
Minimum Qualification: PhD in a relevant technical field.
This is an urgent requirement with an anticipated start date within 2 weeks. Priority will be given to candidates who can interview promptly and begin within two weeks of selection.
Job Summary
We are seeking a highly motivated Machine Learning Research Engineer (ScientificEngineering AI) with strong expertise in Machine Learning, Deep Learning, Computer Vision, and AI research. This role is intended exclusively for PhD graduates or candidates near completion from reputable universities.
Candidates with a strong academic research background in Machine Learning, Artificial Intelligence, Computer Vision, Data Science, Scientific Computing, Mechanical Engineering, Materials Science, Manufacturing Engineering, Applied Physics, Computational Engineering, or related fields are encouraged to apply.
Ideal candidates will combine strong ML/DL expertise with domain knowledge in mechanical engineering, materials science, manufacturing systems, physical systems, scientific computing, or simulation-driven engineering applications.
Research experience gained during a PhD program will be considered equivalent to professional industry experience.
This is an urgent hiring requirement, and we are actively seeking candidates who can start within the next 2 weeks.
Education Requirement 
PhD in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Machine Learning, Data Science, Mechanical Engineering, Materials Science, Manufacturing Engineering, Applied Physics, Computational Engineering, or a related technical field. 
Candidates currently pursuing a PhD with anticipated graduation within the next 3-6 months are also encouraged to apply. 
Only PhD candidates will be considered for this role. 
Candidates with only a Master's degree will not be considered. 
Key Responsibilities 
Design, develop, train, and optimize Machine Learning and Deep Learning models for real-world applications. 
Own the complete ML lifecycle including data collection, annotation, preprocessing, model training, fine-tuning, evaluation, optimization, and deployment. 
Develop and deploy advanced deep learning architectures including CNNs, LSTMs, ConvLSTMs, Graph Neural Networks (GNNs), Reinforcement Learning, and Transformer-based models. 
Conduct experiments, evaluate model performance, and drive continuous algorithmic improvements. 
Work with large-scale datasets for model training, validation, and testing. 
Optimize and deploy AI models for scalable and efficient real-world applications. 
Translate research concepts into scalable, production-ready AI systems. 
Collaborate with cross-functional engineering and research teams to integrate ML models into real-world applications. 
Document methodologies, experimental findings, and technical solutions. 
Contribute to technical innovation initiatives and advanced AI research activities. 
Required Qualifications 
Strong PhD research background in Machine Learning, Deep Learning, Artificial Intelligence, Computer Vision, Data Science, Scientific Machine Learning, Computational Engineering, Applied Physics, Materials Informatics, or related areas. 
Strong programming experience with Python and C++. 
Hands-on experience with PyTorch, TensorFlow, Keras, Scikit-learn, or similar ML frameworks. 
Strong understanding of Machine Learning, Deep Learning, Neural Networks, Computer Vision, and AI algorithms. 
Experience developing and training advanced deep learning models and architectures. 
Solid mathematical foundation in linear algebra, probability, statistics, optimization, and applied machine learning. 
Experience working with Linux environments, Git, Docker, and modern development workflows. 
Demonstrated research experience through publications, thesis work, academic research projects, or equivalent research contributions. 
Strong ability to independently research, prototype, and deploy AI solutions. 
Experience applying machine learning or deep learning techniques to engineering, manufacturing, materials science, physical systems, scientific computing, simulation, or industrial applications is highly desirable. 
Preferred Qualifications 
Publications in leading AI, Machine Learning, Computer Science, Scientific Computing, Computational Engineering, Materials Science, or Applied Physics conferences and journals. 
Experience transitioning AI/ML models from research environments into production systems. 
Experience with CUDA, GPU acceleration, distributed computing, high-performance computing (HPC), or parallel computing environments. 
Experience handling large-scale, real-world datasets. 
Familiarity with Physics-Informed Machine Learning (PIML), Physics-Informed Neural Networks (PINNs), scientific foundation models, digital twins, simulation-driven AI, or engineering optimization techniques. 
Experience working with data generated from CAD, CAE, CFD, FEA, multiphysics simulations, manufacturing processes, materials characterization, laboratory testing, or other engineering and scientific workflows. 
Technical Skills 
Python, C++ 
PyTorch, TensorFlow, Keras, Scikit-learn 
Machine Learning and Deep Learning 
Computer Vision 
Reinforcement Learning 
Graph Neural Networks (GNNs) 
Transformer Architectures 
Linux, Git, Docker 
CUDA and GPU Computing 
Scientific Computing and Optimization 
Physics-Informed Machine Learning (Preferred) 
Engineering and Scientific Data Analysis (Preferred)</div>

Machine Learning Research Engineer (Scientific & Engineering AI)

Accenture in India

<div>
 
 Project Role :
 
 AI / ML Engineer
 
 
 
 Project Role Description :
 
 Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
 
 
 
 Must have skills :
 
 Machine Learning (ML)
 
 
 
 Good to have skills :
 
 NA
 
 
 
 Minimum 3 Year(s) Of Experience Is Required
 
 
 
 
 Educational Qualification :
 
 15 years full time education
 
 
 Role Summary
 
 
 We are seeking a hands-on AI Native Engineer who can design, build, and deploy end-to-end agentic and LLM-powered systems. This includes constructing RAG pipelines, working with vector databases, building autonomous or semi-autonomous agents, integrating tools and skills, and developing evaluation frameworks for high-quality AI behaviour. You will prototype rapidly, experiment with models, and evolve solutions from PoC to production while working closely with cross-functional teams.
 
 
 AI Powered Tech Talent
 
 
 Key Responsibilities
 
 
 Agentic &amp; LLM System Development
 
 
 Build agentic AI systems, including agent orchestration, planning loops, tool calling, and memory modules.
 
 
 Implement LLM toolchains, custom prompts, templates, evaluators, and multi-step reasoning workflows.
 
 
 Develop autonomous/semi-autonomous agents for retrieval, summarization, decision support, or workflow automation.
 
 
 RAG Pipelines &amp; Vector Intelligence
 
 
 Design and implement RAG pipelines end-to-end: ingestion, chunking, embeddings, indexing, vector search, hybrid retrieval, and grounding.
 
 
 Integrate vector databases such as pgvector, Pinecone, Weaviate, or Milvus.
 
 
 Optimize retrieval quality, latency, and factual accuracy using rerankers, retrieval evaluators, and freshness pipelines.
 
 
 Model Integration &amp; AI Ops
 
 
 Integrate enterprise-grade AI APIs, foundation models, and transformer models into scalable systems.
 
 
 Implement robust evaluation frameworks including offline and online evals, regression tests, content safety checks, and red-team scenarios.
 
 
 Build monitoring for model drift, agent failure modes, hallucination detection, and end-to-end system health.
 
 
 Full-Stack &amp; Cloud Alignment
 
 
 Deploy services using Python/Node/Java microservices, serverless functions, or containerized workloads.
 
 
 Integrate event streams, API gateways, and cloud-native patterns across Azure/AWS/GCP.
 
 
 Build CI/CD pipelines for AI services with safe rollouts, versioning, and feature flags for model updates.
 
 
 Prototyping &amp; Rapid Iteration
 
 
 Rapidly experiment with models, embeddings, architectures, and agentic patterns.
 
 
 Translate business requirements into AI-native technical architectures and communicate trade-offs via demos and deep-dives.
 
 
 Document designs, experiments, and evaluation results for reproducibility and knowledge sharing.
 
 
 Professional &amp; Technical Skills
 
 
 Must-Have (AI Native Core)
 
 
 Hands-on experience with LLMs, agent frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, AutoGen), and vector DBs.
 
 
 Strong Python skills for building agents, RAG services, data pipelines, and evaluation harnesses.
 
 
 Deep understanding of transformer models, embeddings, prompt engineering, and model fine-tuning workflows.
 
 
 Experience deploying AI systems to production with monitoring, error handling, retries, and fallback strategies.
 
 
 Good to Have
 
 
 Experience with cloud AI platforms (Azure OpenAI, Bedrock, Vertex AI).
 
 
 Knowledge of multimodal models, reinforcement learning, or advanced reasoning agents.
 
 
 Familiarity with evaluation frameworks (pytest, JUnit) and custom eval harnesses.
 
 
 Additional Information
 
 
 Minimum 3 years of experience in ML/AI engineering (AI-native experience preferred).
 
 
 Location: Bengaluru.
 
 
 Education: 15 years full-time education., 15 years full time education
</div>

AI / ML Engineer

Qualcomm

<div>
 
 Company
 
 
 
 Qualcomm Middle East Information Technology Company LLC
 
 
 
 Job Area
 
 
 
 Engineering Group, Engineering Group &gt; Software Engineering
 
 
 
 General Summary
 
 
 
 
 About Us
 
 
 
 Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region
 
 .
 
 As Saudi Arabia accelerates its digital transformation under Vision 2030, Qualcomm is investing in world‑class computing and data centre capabilities to power AI, cloud, and advanced connectivity at scale. This is a unique opportunity to work in a fast‑growing technology hub, supporting critical environments and helping shape the future of data centre operations in the Kingdom and beyond.
 
 
 
 About The Role
 
 
 
 We are seeking a Staff‑level ML Applications Engineer with deep hands‑on experience in C++/Python‑based AI development in a Linux environment. The ideal candidate operates with a high degree of autonomy, defines technical goals and scope for assigned problem areas, and leads development efforts through execution. This role requires strong analytical skills, effective cross‑team collaboration, and the ability to mentor and guide other engineers by example while remaining hands‑on and execution‑focused.
 
 
 
 We are looking for 8+ years Software Engineering or related work experience
 
 
 
 
 Key Responsibilities Will Include
 
 
 
 <ul>
 <li>
 Improve and optimize key Deep Learning models on Qualcomm AI 100
 </li>
 <li>
 Build deep learning framework extensions for Qualcomm AI 100 in upstream open-source repositories
 </li>
 <li>
 Collaborate and interact with internal teams to analyze and optimize training and inference for deep learning
 </li>
 <li>
 Build software tools and ecosystem around AI SW Stack.
 </li>
 <li>
 Work on Triton, ExecuTorch, Inductor, TorchDynamo to build abstraction layers for inference accelerator.
 </li>
 <li>
 Optimize workloads for both scale-up (multi-SoC) and scale-out (multi-card) systems
 </li>
 <li>
 Optimize the entire deep learning pipeline including graph compiler integration
 </li>
 <li>
 Apply knowledge of software engineering best practices.
 
 
 
 </li>
 </ul>
 
 Desirable Skills And Aptitudes
 
 
 
 
 Required Skills and Aptitude
 
 
 
 <ul>
 <li>
 Deep Learning experience or knowledge &ndash; LLMs, Natural Language Processing, Vision, Audio, Recommendation systems
 </li>
 <li>
 Excellent C/C++ Or Python programming and software design skills, including debugging, performance analysis, and test design.
 </li>
 <li>
 Very strong hold on Pytorch and JIT.
 </li>
 <li>
 Well versed with open-source development practices.
 </li>
 <li>
 Ability to work independently, define requirements and scope, and lead a development effort.
 </li>
 <li>
 Mentors and guides team members through influence and example, without direct people‑management responsibility
 </li>
 <li>
 Avid problem solver &ndash; should be able to find solutions to key engineering and domain problems.
 </li>
 <li>
 Strong developer with a research mindset &ndash; strives to innovate.
 
 
 
 </li>
 </ul>
 
 Preferred Skills
 
 
 
 <ul>
 <li>
 Experiences to run workloads on large scale heterogeneous clusters is a plus
 </li>
 <li>
 Knowledge of compiler is a plus.
 </li>
 <li>
 Hands-on experience with CUDA, CUDNN is a plus.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's / Masters/ PHD degree in Engineering, Machine learning/ AI, Information Systems, Computer Science, or related field.
 </li>
 <li>
 8+ years Software Engineering or related work experience.
 </li>
 <li>
 2+ years experience with Programming Language such as C++, Python.
 
 
 
 </li>
 </ul>
 
 What's On Offer
 
 
 
 Apart from working with great people, we offer the below:
 
 
 <ul>
 <li>
 Salary including housing &amp; transport allowance
 </li>
 <li>
 Stock (RSU's) and performance related bonus
 </li>
 <li>
 16 weeks fully paid Maternity Leave
 </li>
 <li>
 6 weeks fully paid Paternity Leave
 </li>
 <li>
 Employee stock purchase scheme
 </li>
 <li>
 Child Education Allowance
 </li>
 <li>
 Relocation and immigration support (if needed)
 </li>
 <li>
 Life and Medical Insurance
 </li>
 <li>
 Live+ Well Reimbursement for health and recreational membership fees
 
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
 
 </li>
 </ul>
 OR
 
 
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
 
 
 OR
 
 
 PhD in Engineering, Information Systems, Computer Science, or related field.
 
 
 <ul>
 <li>
 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.
 </li>
 <li>
 References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
 
 
 
 </li>
 </ul>
 Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
 
 
 Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
 
 
 
 To all Staffing and Recruiting Agencies
 
 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
 
 
 If you would like more information about this role, please contact Qualcomm Careers.
</div>

Machine Learning Engineer, Staff level (Datacentre AI Engineering) - Riyadh, KSA

Pika

<div><h3 class="jobSectionHeader">About the Role</h3>
We are seeking a Senior Inference Engineer to accelerate the performance of Pika's AI-driven products. In this highly technical role, you will operate at the intersection of cutting-edge inference acceleration, GPU parallelism, advanced model deployment, and video generation technologies. Your expertise will drive significant improvements to model speed and efficiency, ensuring our creative AI systems deliver industry-leading user experiences at scale.<div></div> 
You will design and optimize inference pipelines, implement state-of-the-art acceleration techniques, and work closely with researchers and engineers across the team to push the boundaries of what&rsquo;s possible in real-time AI deployment. Your efforts will play a foundational role in powering the next generation of Pika&rsquo;s video and language models.<div> 
</div><h3 class="jobSectionHeader">
What You&rsquo;ll Do</h3><ul><li>
Accelerate Inference: Lead and implement advanced inference acceleration techniques, including attention optimization and quantization for efficient model serving.</li><li>
Maximize GPU Parallelism: Engineer and optimize GPU strategies across tensor, sequence, and pipeline parallelism (TP, SP, PP) for maximal efficiency and scalability.</li><li>
Programming for Performance: Develop and optimize high-performance computing kernels and distributed workloads using CUDA and NCCL.</li><li>
Advance AI Deployment: Collaborate with research and engineering teams to bring state-of-the-art videogen and large language models into production.</li><li>
Improve Training Efficiency: (Bonus) Contribute to improvements in model training speed, stability, and resource utilization as part of our deployment lifecycle.</li><li>
Technical Excellence: Drive rigorous code reviews, participate in technical discussions, and mentor fellow engineers on best practices in inference and GPU programming.</li></ul><div> 
</div><h3 class="jobSectionHeader">
What We&rsquo;re Looking For</h3><ul><li>
Experience: 5+ years engineering experience, with a strong track record in inference acceleration and model deployment at scale.</li><li>
Inference Mastery: Proven expertise in inference optimization, including quantization, attention acceleration, and deep learning compiler stacks.</li><li>
GPU &amp; Parallelism: Deep knowledge of GPU programming (CUDA, NCCL) and experience with SP, TP, PP, and other forms of parallelism for distributed inference.</li><li>
AI Domain Knowledge: Familiarity with video generation (videogen) models and large language models (LLMs).</li><li>
Collaboration: Strong cross-discipline communication skills; able to drive shared goals across research and engineering functions.</li><li>
Ownership Mindset: Self-driven, solutions-oriented, and capable of managing ambiguity in a fast-paced startup environment.</li><li>
Bonus: Experience in enhancing training efficiency, stability, or resource optimization for large models.</li></ul><div> 
</div><h3 class="jobSectionHeader">
Nice to Have</h3><ul><li>
Experience with high-throughput video or real-time streaming model deployment</li><li>
Familiarity with distributed training and optimization toolkits</li><li>
Contributions to open source projects in AI infrastructure or deep learning compilers</li><li>
Startup or rapid prototyping experience</li></ul><div> 
</div><h3 class="jobSectionHeader">
What We Offer</h3><ul><li>
Competitive salary in the AI industry</li><li>
Equity in a fast-growing startup shaping the future of AI</li><li>
Comprehensive health benefits, monthly stipends, company retreats</li><li>
A supportive and collaborative office culture&mdash;we&rsquo;re all building and launching together</li></ul><div> 
</div><h3 class="jobSectionHeader">
About Pika</h3>
At Pika, we're crafting a future where video creation is seamless, intuitive, and universally accessible. Our mission is to empower creativity by breaking down technical barriers using the transformative power of AI. We&rsquo;re a tight-knit, energetic team based in Palo Alto, CA, valuing efficiency, curiosity, and the ambition to make a meaningful impact on the world.<div></div> 
We work from our Palo Alto office 3&ndash;5 days a week and welcome applicants who are eager to contribute onsite.
Compensation Range: $185K - $250K</div>

Senior Software Engineer, Inference

Mistral

<div>
 
 About Mistral
 
 
 
 At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.
 
 
 We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, La Plateforme, Mistral Code and Mistral Compute - a suite that brings frontier intelligence to end-users.
 
 
 We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.
 
 
 Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.
 
 
 Role Summary
 
 
 
 About The Research Engineering Team
 
 
 
 The team spans
 
 Platform
 
 (shared infra &amp; clean code) and
 
 Embedded
 
 (inside research squads). Engineers can move along the research&harr;production spectrum as needs or interests evolve.
 
 
 As a Research Engineer &ndash; ML track, you&rsquo;ll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you&rsquo;ll either join:
 
 
 <ul>
 <li>
 Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or
 </li>
 <li>
 Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, &hellip;) and turn fresh ideas into repeatable, scalable code
 
 
 
 </li>
 </ul>
 What will you do
 
 
 <ul>
 <li>
 Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools
 </li>
 <li>
 Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs
 </li>
 <li>
 Conduct experiments on the latest deep-learning techniques (sparsified 70 B + runs, distributed training on thousands of GPUs)
 </li>
 <li>
 Design, implement and benchmark ML algorithms; write clear, efficient code in Python
 </li>
 <li>
 Deliver prototypes that become production-grade components for Le Chat and our enterprise API
 
 
 
 </li>
 </ul>
 
 About You
 
 
 
 <ul>
 <li>
 Master&rsquo;s or PhD in Computer Science (or equivalent proven track record)
 </li>
 <li>
 4 + years working on large-scale ML codebases
 </li>
 <li>
 Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s)
 </li>
 <li>
 Experience in deep learning, NLP or LLMs; bonus for CUDA or data-pipeline chops
 </li>
 <li>
 Strong software-design instincts: testing, code review, CI/CD
 </li>
 <li>
 Self-starter, low-ego, collaborative
 
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 💰 Competitive salary and equity
 </li>
 <li>
 🚑 Healthcare: Medical/Dental/Vision covered for you and your family
 </li>
 <li>
 👴🏻 Pension : 401K (6% matching)
 </li>
 <li>
 🏝️ PTO : 18 days
 </li>
 <li>
 🚗 Transportation: Reimburse office parking charges, or $120/month for public transport
 </li>
 <li>
 🏀 Sport: $120/month reimbursement for gym membership
 </li>
 <li>
 🥕 Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)
 </li>
 <li>
 🌎 Visa sponsorship
 </li>
 <li>
 🤝 Coaching: we offer BetterUp coaching on a voluntary basis
 
 
 
 </li>
 </ul>
 By applying, you agree to our Applicant Privacy Policy.
</div>

Research Engineer, Machine Learning

Tesla

<div>What to Expect<div>
As a Machine Learning Engineer on the Bottle Rocket team, you will play a critical role in developing innovative, data-driven solutions on Tesla&rsquo;s generative AI platform. You will focus on leveraging machine learning models and deep learning techniques to solve complex problems and deliver impactful insights. Collaborating with cross-functional teams, you&rsquo;ll translate research concepts into scalable data products and drive data-centric strategies for optimizing AI applications. Your work will ensure the effective use of generative AI across diverse business challenges, enabling transformative outcomes that align with Tesla&rsquo;s innovative mission.
Expect a dynamic, fast-paced environment where innovation and collaboration are paramount, and every improvement you make has a direct impact on advancing some of the most ambitious technological goals in the industry.</div> 
What You'll Do<div><ul><li>
Design, develop, train, and deploy machine learning solutions that leverage generative AI technologies, such as Large Language Models (LLMs)</li><li>
Analyze and improve the accuracy, efficiency, and scalability of AI models through rigorous data-driven experimentation, evaluation, and iterative model training processes</li><li>
Work closely with software engineers to productionize machine learning models and integrate them into scalable, reliable systems</li><li>
Optimize data pipelines and workflows to enable high-performance AI applications, leveraging specialized hardware when appropriate</li><li>
Deliver robust, high-impact data products that inform decision-making and enhance the capabilities of the generative AI platform</li><li>
Conduct research and remain up-to-date on the latest developments in AI/ML, with a special focus on generative AI, to rapidly test and prototype new ideas</li><li>
Convert complex business requirements and research findings into actionable insights and data-driven solutions</li></ul>
</div> 
What You'll Bring<div><ul><li>
Proven experience in applying machine learning and AI techniques to solve real-world problems, particularly with generative AI and LLMs</li><li>
Strong proficiency with Python-based machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, JAX, TGI/vLLM, NumPy)</li><li>
Demonstrated ability to take research prototypes and deploy them as scalable, production-grade systems</li><li>
Expertise in working with and optimizing large datasets, data pipelines, and AI models</li><li>
Experience building robust, reliable solutions that minimize downtime and maximize user impact</li><li>
A problem-solving mindset, with strong attention to detail and a true follower of Occam's razor when designing and implementing solutions</li></ul>
</div> 
Compensation and Benefits<div>
Benefits</div><div>
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
<ul><li>Medical plans &gt; plan options with $0 payroll deduction</li>
<li>Family-building, fertility, adoption and surrogacy benefits</li>
<li>Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution</li>
<li>Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA</li>
<li>Healthcare and Dependent Care Flexible Spending Accounts (FSA)</li>
<li>401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits</li>
<li>Company paid Basic Life, AD&amp;D</li><li>
Short-term and long-term disability insurance (90 day waiting period)</li>
<li>Employee Assistance Program</li>
<li>Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays</li>
<li>Back-up childcare and parenting support resources</li>
<li>Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft &amp; legal services, and pet insurance</li>
<li>Weight Loss and Tobacco Cessation Programs</li>
<li>Tesla Babies program</li>
<li>Commuter benefits</li>
<li>Employee discounts and perks program</li>
</ul></div><div>Expected Compensation</div><div>
$140,000 - $300,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.</div> 
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws. 
 
Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.</div>

Staff Machine Learning Engineer, AI Infrastructure

NXP Semiconductors

<div>We at NXP have an environment that fosters innovation. Our team has technology experts who understand the big picture and mentors who coach passionate professionals to work on the most exciting challenges. We share responsibilities in everything we do, where every point of view is valued. Join us! 
Job Summary 
We are seeking a highly skilled Edge AI Engineer/Scientist with a strong theoretical foundation in AI and solid software engineering expertise to contribute to our Edge AI Model Optimization program. While the primary focus of this role is on model quantization, the scope also includes complementary optimization strategies such as speculative decoding, pruning, and other methods for ensuring highly efficient on-device deployment. 
You will work at the forefront of innovation, bridging the gap between research and practice, focusing on CNNs, Large Language Model (LLM) and Vision Language Model (VLM) optimization to bring advanced capabilities to NXP&rsquo;s Ara2 family of NPUs, directly supporting the future of on‑device intelligence. 
If you want to the future of efficient on‑device AI, this is the place to be. 
Job Responsibilities 
Research: Actively survey the latest research (NeurIPS, ICLR, CVPR) on model optimization/compression, focusing particularly on neural network quantization, but also including other techniques like speculative decoding, pruning, etc.
 
Prototyping: Develop and adapt state-of-the-art methods to NXP&rsquo;s hardware constraints, building POCs to showcase the effectiveness of these techniques on NXP HW.
 
Production Implementation: Translate research prototypes into robust, optimized production code (C++/Python), ensuring strict memory and compute efficiency standards.
 
Systems Integration: Document algorithmic tradeoffs, derive deployment recipes, and mentor the engineering team on numerical methods and optimization.
 
Cross-Functional Leadership: Act as the technical bridge between AI Research, Hardware Engineering and other teams, providing quantified guidance on how choices impact model accuracy and performance.
 
IP Generation: Contribute to NXP&rsquo;s intellectual property portfolio through patents and technical publications. 
Job Qualifications 
Required Background 
Education: MSc or Ph.D (is a plus) in Computer Science, Electrical Engineering, or Mathematics with a focus on Machine Learning or Deep Learning.
 
AI Expertise: Proven practical experience in AI/ML with a deep understanding of CNN architectures and Generative AI (Transformers, LLMs, VLMs, etc.).
 
Technical Stack: Strong hands-on experience with PyTorch, ONNX, and model conversion/optimization pipelines.
 
Software Engineering: Proficient in Python and C++ and best development practices.
 
Embedded Mindset: Familiarity with the constraints of embedded systems (latency, power, memory bandwidth) and how code interacts with underlying hardware. 
Preferred 
Advanced AI: Experience with state-of-the-art quantization techniques for discriminative and generative AI (e.g., GPTQ, SpinQuant, etc).
 
Hardware Acceleration: Experience with NPUs, device-level profiling, and diagnosing memory bottlenecks.
 
Kernel Development: Experience with custom kernel development is a plus.
 
Compilers: Knowledge of MLIR or TVM is a significant plus. 
 
More information about NXP in India...
#LI-29f4</div>

Senior Quantization Engineer - Edge AI Model Optimization

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