23 training jobs found in Palo Alto

As a Software Engineer within the Autopilot AI Infrastructure team, you will work on reinforcing, optimizing, and scaling our infrastructure components supporting AI research activities for Autopilot and the Optimus. At the core of our autonomy capabilities are neural networks that the research team is designing to train on very large amounts of data, across large-scale GPU clusters. Robustly training these models at scale and in the shortest amount of time is critical to our mission. The Role Reduce wall clock time to convergence of our training jobs by identifying bottlenecks in the ML stack, from data-loading up to the GPU Integrate efficient, low-level code with the overall high-level training framework Profile our workloads and implement solutions to increase training efficiency Optimize workloads for efficient hardware utilization (e.g. CPU and GPU compute, data throughput, networking) Requirements Members of the Autopilot AI Infrastructure...

As a Software Engineer within the Autopilot AI Infrastructure team, you will work on reinforcing, optimizing, and scaling our infrastructure components supporting AI research activities for Autopilot and the Optimus. At the core of our autonomy capabilities are neural networks that the research team is designing to train on very large amounts of data, across large-scale GPU clusters. Robustly training these models at scale and in the shortest amount of time is critical to our mission. We are building and improving the in-house distributed training framework used by the research team to train production models, ensuring good ergonomics and flexibility for experimentation while providing good stability and performance. The Role Write robust Python software code in our machine learning training repository while applying best software practices to support the research team Increase the reliability of our training jobs by debugging and root causing failures across...

Tesla Sourcers find top software talent to power a abundant & autonomous future. This role partners closely with Recruiters, Engineers, and Engineering Managers to identify, attract, and assess exceptional candidates. We're hiring top software engineers to build the systems behind Tesla's most ambitious work. From custom chip design and AI inference to training and deploying large-scale models, we're shaping the software that powers autonomy at scale. At the same time, we're shaping the future of mobility - hiring engineers to design and ship the firmware, distributed systems, and core software that enables Robotaxi fleet operations and network-wide deployment. This is where software talent drives every layer of the stack, turning innovation into real-world impact. We're looking for the next generation of builders to join us. The Role Utilize multiple tools and approaches, including AI-driven sourcing techniques, to identify and engage top talent Build robust software...

As a Software Engineer on Tesla AI's RL Infrastructure team, you will build the systems that make large-scale reinforcement learning fast, stable, and flexible for ML engineers working on real-world AI problems. Your work on RL training will be critical for scaling Robotaxi and Optimus. We're looking for someone with practical experience in GPU inference performance, RL training infrastructure, or both. Your work will directly impact iteration speed, training throughput, system reliability, and the ability of ML engineers to move from prototype to large-scale experiments quickly. The Role Build infrastructure for large-scale reinforcement learning Improve performance and scalability of RL workloads Optimize training and inference latency, throughput, memory usage, and hardware utilization Develop tools for benchmarking, profiling, debugging, and monitoring Work closely with ML engineers to productionize new methods and workflows Debug bottlenecks...

The Performance Optimization team takes research models and makes them run efficiently on Tesla's AI-ASICs, powering Autopilot and Optimus. This role sits at the intersection of AI research, compiler development, kernel optimization, and hardware design. You'll collaborate with AI researchers on novel quantization techniques, precision improvements, and non-standard architectures. You'll develop optimized kernels using our MLIR-based compiler stack to achieve real-time latency for self-driving and humanoid robots. You'll work directly with hardware teams to shape our next-generation AI5, AI6, and Dojo3 chips. The Role Implement, optimize, and profile highly performant kernels for inference and training on Tesla's AI and Dojo ASICs Optimize bottlenecks in the inference flow, make precision/performance tradeoff decisions, and develop novel techniques to improve hardware utilization and throughput Work on a variety of edge and datacenter workloads, from small...

As a Software Engineer within the Autopilot AI Infrastructure team, you will work on reinforcing, optimizing, and scaling our infrastructure components supporting AI research activities for Autopilot and the Optimus. At the core of our autonomy capabilities are neural networks that the research team is designing to train on very large amounts of data, across large-scale GPU clusters. Robustly training these models at scale and in the shortest amount of time is critical to our mission. We are building out the Machine Learning Platform that our engineers and leadership use to schedule, manage and monitor machine learning experiments, data pipelines and artifacts. The Role Architect and implement scalable, user-friendly tools for AI workflows to track and visualize the lifecycle of machine learning experiments and models Build robust tools and infrastructure to improve the machine learning team's velocity. This includes training and evaluation code in Python to...

As a Software Engineer within the Autopilot AI Infrastructure team, you will work on reinforcing, optimizing, and scaling our infrastructure components supporting AI research activities for Autopilot and the Optimus. At the core of our autonomy capabilities are neural networks that the research team is designing to train on very large amounts of data, across large-scale GPU clusters. Robustly training these models at scale and in the shortest amount of time is critical to our mission. We are building out the Machine Learning Platform that our engineers and leadership use to schedule, manage and monitor machine learning experiments, data pipelines and artifacts. With the ever-increasing size of our datasets and compute clusters, we are looking for an experienced backend engineer to help drive scalability improvements and new capabilities in the platform. The Role Develop and deploy solutions to scale our infrastructure effectively in response to rapidly growing demands...

As a member of the Autopilot AI Tooling team you will design and implement a diverse set of tools that power our machine learning workflows. You will work closely with some of the best, world-class AI researchers and machine learning experts towards Tesla's goal of a self-driving future. The AI Tooling team is a central part of Autopilot AI. The systems you build will have a large impact on the entire lifecycle of model development. This includes data processing, data discovery, annotation, and visualization. This also includes tools that help us automate the entire workflows of training, validation, and productionization of our Autopilot neural networks. As an Engineer on the AI Tooling team, you bring top-notch software engineering skills and can contribute to our tooling systems immediately. Knowledge of machine learning, computer vision, or neural networks is a plus but not required. That can be learned on the job as you work with our machine learning experts. A strong...

We are looking for strong software engineers to help scale the next generation of large AI models for Autopilot, Optimus & Digital Optimus. This role sits at the intersection of distributed systems, machine learning, and performance engineering. You will work closely with ML practitioners and infrastructure engineers to improve training efficiency, accelerate experimentation, and enable larger and more capable models. The ideal candidate is excited about both systems and machine learning. You should be comfortable debugging distributed training issues, analyzing model behavior, and using data to demonstrate how infrastructure improvements translate into better model quality. You will help build and optimize large-scale training systems running on thousands of GPUs while developing the tools, metrics, and workflows needed to make model scaling faster and more predictable. The Role Optimize large-scale distributed training across thousands of GPUs...

The AI Deployments team builds systems that enable rapid model iteration and dynamic deployment of AI onto end-user hardware platforms across Vehicle, Robotaxi, Optimus, and Digital Optimus. Our infrastructure is the fastest way to evaluate Tesla's AI in the real world. Our mission is to make it the standard - even faster, more robust, and seamless. Beyond speed, our systems are core to 24/7 Optimus model evaluation, reinforcement learning flows, driving vehicles autonomously off factory lines, and seamless deployment and model weights installation on Tesla products around the world. The team lives at the intersection of cloud services, build systems, on-device tasks, OTA infrastructure, AI model runtime, networking, and security. Your work will directly accelerate FSD and Optimus programs and set the new standard for how models ship to millions of Tesla vehicles and robots worldwide. The Role Design and build high-impact systems - cloud, delivery, device - that...

As a member of the Autopilot AI Tooling team, you will design and implement a powerful, diverse set of tools that fuel our machine learning workflows and propel Robotaxi and Optimus forward. You'll work side-by-side with some of the world's best AI researchers and machine learning experts, driving Tesla's mission toward a fully self-driving future. The systems you build will have a direct, high-impact effect on our fleet's ability to sense, perceive, and understand the world around it. Our tools automate the entire end-to-end workflows of training, validation, and production of Autopilot neural networks and Optimus - accelerating progress at a massive scale. As an Engineer on the AI Tooling team, you'll bring elite software engineering skills to make an immediate contribution to our critical tooling systems. Knowledge of machine learning, computer vision, or neural networks is a plus but not required. Strong candidates are either outstanding software generalists or...

Tesla is looking for an experienced, full-stack Software Engineer to contribute to the development of the data factory and software services for our cutting-edge battery products. This position will help drive technological advancement by delivering data and software solutions to solve high-volume manufacturing problems. Battery development is at the heart of Tesla's mission, and this is an exciting opportunity to address the central challenges in scaling electric vehicle manufacturing and to see the physical impact of your work. Tesla is a demanding and fast-paced environment where you will work with a highly motivated team on extremely challenging projects. The Role Lead the design and development of our model training infrastructure for advanced Data Science applications in manufacturing Collaborate with engineers across multiple departments on model design and hardware selection for efficient compilation and execution Build scalable and reliable pipelines to...

The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla's machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system. The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life. As a key member of the Tesla AI hardware team, the AI/ML Modeling Engineer will drive the modeling, and optimization of next-generation tensor compute hardware. This role requires a deep expertise in computer...

As a Software Engineer within the Supercomputing AI Infrastructure team, you will work on scaling and optimizing our training compute clusters at the core of Robotaxi and the Optimus development. Tesla Supercomputing maintains, on premise, some of the largest supercomputers in the world. We're currently scaling 100K+ GPU clusters, which are central to developing our autonomy capabilities. Robustly managing such a large system of AI training and HPC clusters requires software design through the stack: from the operating system to workload scheduling to ultimately the training loop. We are building and improving the workload scheduling systems that govern how hundreds of thousands of GPUs are allocated across training jobs, experiments, and data pipelines. In this role, you will own the Slurm-based scheduler at the heart of our AI HPC compute infrastructure, ensuring that cluster resources are utilized efficiently and that engineers can iterate quickly without friction The Role...

Tesla's AI Infrastructure team builds the software that turns GPUs and custom silicon into reliable, efficient training capacity for Autopilot, Optimus, Robotaxi, and Dojo. We own the systems layer between bare metal and researchers: cluster lifecycle, fleet automation, observability, scheduling interfaces, and the control-plane software that keeps multi-node training jobs healthy at scale. In this role, you'll work as a software engineer in a high-performance environment, shipping production services and tooling that operate thousands of accelerated machines, not only configuring them by hand. You'll design, build, and operate software that provisions, monitors, heals, and optimizes our AI training fleets. You treat the cluster as a product: APIs, automation pipelines, reliability signals, and abstractions that make supercomputing capacity safe and fast for ML users. You'll focus on distributed-systems and systems-software problems (hosts, accelerators, fabric, storage,...

Our team productionizes and experiments with novel ML models for our custom HW- we train and deploy large neural networks for efficient inference on compute-constrained edge devices (CPU / GPU / AI ASIC). The nature of this role is multi-disciplinary - you will work at the intersection of machine learning and systems by building the co-designing ML models and their developing the associated deployment infrastructure that enables the seamless training, deployment, and inference of all neural networks that run at Tesla AI. The Role Build robust AI frameworks to lower neural networks to edge devices Build robust AI infrastructure to train and fine-tune networks for Autopilot and Optimus on large GPU clusters Deploy state-of-the-art neural networks on heterogenous compute, including Tesla's in-house AI ASIC, with an aim to maximize network performance while minimizing latency Collaborate with AI scientists and compiler engineers to effectively compress large models...

Our team productionalizes ML models - we train and deploy large neural networks for efficient inference on compute-constrained edge devices (CPU / GPU / AI ASIC). The nature of this role is multi-disciplinary - you will work at the intersection of machine learning and systems by building the ML frameworks and infrastructure that enable the seamless training, deployment, and inference of all neural networks that run on Autopilot and Optimus. The Role Build robust AI frameworks to lower neural networks to edge devices Build robust AI infrastructure to train and fine-tune networks for Autopilot and Optimus on large GPU clusters Deploy state-of-the-art neural networks on heterogenous compute, including Tesla's in-house AI ASIC, with an aim to maximize network performance while minimizing latency Collaborate with AI scientists and compiler engineers to effectively compress large models to run in low precision Design and implement custom GPU kernels (CUDA /...

As a member of the AIHW Infra team, you will play a critical role in supporting Tesla's AI hardware initiatives by developing automation, infrastructure, and services. Join a dynamic team of engineers dedicated to accelerating workloads through collaboration with AI HW design teams and High-Performance Computing (HPC) groups. Your primary focus will be building robust infrastructure solutions, while also assisting in debugging performance bottlenecks and root-causing cluster issues as needed. The ideal candidate is a proactive engineer with a passion for creating scalable, efficient systems. The Role Developing Python libraries to automate, monitor, measure, and troubleshoot workflows on AI hardware infrastructure Spending approximately 50% of time building automation and infrastructure, primarily in Python and other languages, with the remaining time focused on debugging, experimentation, and resolving infrastructure challenges and performance bottlenecks...

Tesla AI's Agentic Tooling team builds the harness and skill ecosystem for the AI org powering FSD and Optimus. Our agents already do real engineering work day-to-day for engineers across the org. We own the customized harness end-to-end: the orchestration around model backends, the tool ecosystem agents call into, the session and memory layer, the observability stack, and the evaluation system that gates every prompt, skill, and model upgrade. You'll work across the full surface of the team, extending the harness, shipping new skills, building evaluations, owning observability, and picking up whatever is most leveraged each quarter. Models and skills evolve weekly, so a fast iteration loop and honest measurement of what you ship are non-negotiable. The Role Harness development: Extend the agent runtime and tool ecosystem end-to-end. Add new tools, integrations, and backends without regressing existing skills, and keep the platform easy to extend as the ecosystem evolves...

Tesla uniquely builds foundational AI that moves beyond pixels and through the physical world - delivering this at scale requires general-purpose robots (Robotaxis & Optimus) capable of navigating complex environments with high precision. Every millisecond counts, as rapid perception & decision-making enables swift responses to dynamic conditions. This is where our Foundations team comes in - we combine low-level software techniques with modern C++ code to optimize the latency, throughput, and memory of our onboard camera & vision stack. Our work directly enhances both the safety & efficacy of Full-Self-Driving (FSD) as well as humanoid dexterity; this is key to expanding the Robotaxi fleet globally and advancing Optimus' ability to perform intricate real-time tasks with near-human accuracy. The Role Write, debug and maintain robust C/C++ code underpinning the entire FSD & Optimus software suite; depending on needs and your interests/skills, you might work on code related...