Tech Lead Manager ML Optimization
$298k - $378kWaymo
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The Waymo ML Infrastructure team accelerates Waymo’s mission, by building the best ecosystem for sustainably innovating and shipping ML powered intelligence.
Research, Production, and the Hardware teams are our primary stakeholders and our work powers the development of the state of the art models in the areas of Perception and Trajectory planning that are core to our autonomous driving software. We enable our partners by offering the best in class solutions for the entire model development lifecycle. These solutions include understanding the model business goals and platform hardware characteristics, and codesign the models for the hardwares. These solutions are developed in close collaboration with teams at different modeling teams. Scale and efficiency are core tenets our infra follows.
We are looking for an experienced senior TLM to join our team. In this critical role, you will lead the development and enable efficient deployment for large-scale machine learning models using state of the art advanced AI infrastructure. You will work cross functionally at the intersection of data engineering, model development, and Datacenter + on-device low-latency deployments, ensuring seamless integration across teams and technologies to power efficient innovation.
You will
Take ownership of improving model efficiency on different platforms and drive the model system codesign practice that meet both technical and business requirements. You will work with cutting-edge ML models that may consist of multiple billions of parameters, and apply your expertise in model optimizations and advanced algorithms toward efficient execution and deliver results on multiple hardware compute platforms.
The key responsibilities for this role include:
- Technical Leadership: Proactively study the SOTA model architectures and optimizations from the community and Google, for World Models, Diffusion + flow matching techniques, and translate them into measurable technical deliverables in Waymo’s onboard driving stack.
- Performance Analysis: Dev tooling innovation for model performance inspector in highly distributed training/inference setups, apply roofline analysis, understand the efficiency headrooms and drive work groups to deliver the optimizations and meet the system requirements.
- Strong Execution: Innovate high performance optimizations and tools for various models and large-scale training/inference including on future next-gen TPUs and low-bit precision training/inference setup, and ensure all system components align towards achieving high performance and goodput goals.
- Cross-Team Leadership: Guide efforts across multiple teams and organizations to ensure seamless integration of data generation, model development, and deployment pipelines.
- Mentorship & Management: Act as a mentor to junior engineers, helping to grow their technical expertise and foster a culture of collaboration and engineering excellence. Manage the IC performance for a medium size team of ~10 engineers.
You Have
- 10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, training, deploying, and optimizing large-scale machine learning systems.
- Experienced using ML accelerator profiling tools to uncover performance bottlenecks.
- Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, JAX, or similar frameworks.
- Deep understanding of state-of-the-art machine learning models and architectures such as autoregressive and diffusion transformers and familiarity with custom-kernels for diverse h/w compute based efficiency.
- Strong leadership skills with experience navigating cross-functional teams and providing technical leadership projects across multiple organizations.
- Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience.
- A Master’s or PhD in Computer Science, Engineering, or a related field is preferred.
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range
$298,000—$378,000 USD
$262k - $364k
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...performance GPU infrastructure across AI/ML, visual effects, rendering, and real-time... ...Performance team, focused on kernel authoring and optimization. You will write, profile, and tune the... ...will also aid us in achieving industry-leading end-to-end performance benchmarking...Permanent employmentTemporary workCasual workWork at officeFlexible hours- ...avatar-led generation to testing, optimization, and publishing across Meta,... ...users across 10,000+ teams. Leading brands—including Alibaba, HubSpot... ...work on large-scale applied ML problems, build state-of-the-... ...production. ~ Prior experience in a tech lead (TL) capacity, such as...Full time
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Tech Lead, YouTube Shorts Discovery, ML Recommendations link Copy link corporate_fare YouTube place Mountain View... ...or retrieval systems. Expertise in managing the cold-start problem,... ...solutions in specialized ML areas, optimize ML infrastructure, and guide the development...$228k - $285k
...foundational pillar of the Autonomy stack. In this Tech Lead (TL) role, you will own, architect,... ...also own and drive the whole end‑to‑end ML lifecycle & data flywheel for these... ..., evaluation, model performance optimization, feedback loop. You will also represent...Full timeContract workLocal area- Rivian is seeking a Tech Lead for mapping within its Autonomy group in California. You will own... ...ship production-grade pipelines and own the ML data flywheel, from data collection to model evaluation and performance optimization. You will define system requirements, guide...
$238k - $302k
...report to a Senior Staff Engineer, Technical Lead Manager. You will: Develop ADV's... ...teams to codesign hardware/software and optimize the software for best performance on our... ...techniques, frameworks (SIMD/CUDA) and ML performance/frameworks Experience...Full timeRemote work$240k - $333k
...impairments, including noise, ISI, and high-frequency jitter profiles.Lead the debugging of RTL and environment failures, collaborating... ...methodologies.In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive...WorldwideShift work$187k
...experience in this always-on, high-tech, and hyper-connected world.... .... You are expected to be a leading expert in one or multiple areas... ...the-art technologies, including ML, DL and large language model.... ..., improve, automate and optimize distributed systems and tools....Temporary workFlexible hours$262k - $365k
...experience in a technical leadership role leading project teams and setting technical... ...within a mission‑driven team. As a Tech Lead Manager (TLM) for the Gemini App Personalization... ...system instruction authoring and optimization, model serving configuration, and experiment...- Applied Intuition Inc. is seeking a software engineer with deep expertise in optimizing ML models for production-grade embedded runtime environments. You will work across the ML framework stack and target a range of embedded compute platforms used in on- and off-road ADAS...
- ...a Software Engineer in Sunnyvale, California, with expertise in optimizing machine learning models for embedded systems. This role involves... ...optimization for embedded compute platforms, collaborating with ML engineers, and requires strong software development skills. The...
$166k - $244k
...more of the following: Machine Learning Optimization (e.g., quantization, distillation), GPU/TPU... ..., or specialization in another ML field. 3 years of experience with ML infrastructure... ...performance without loss of quality. Lead low‑level performance optimization efforts...Full timeTemporary work- ...is seeking a Senior Software Engineer, AI/ML, Ads Training in Mountain View to advance... ...systems and TPU efficiency. You will lead initiatives to migrate Ads models to JAX,... ...improve scalability, and drive cross-stack optimizations with robust debugging infrastructure. The...
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...Softbank, Fidelity, T. Rowe Price, and other leading investorsAbout the RoleNuro takes a... ...to autonomous driving technology. In an ML-first system, the overall system performance... ...cutting-edge ML research to automate and optimize the data labeling lifecycleAbout YouYou have...Immediate startFlexible hours- Gleanwork is seeking a Tech Lead Manager for its Agentic Runtime team in Mountain View, California. This role focuses on building a low-latency, reliable foundation for Glean's AI agents, optimizing cost and reliability while ensuring secure operations. The ideal candidate...Work at office
- ...limits of what's possible.As a Lead Software Engineer at... ....Own infrastructure capacity optimization solutions and build predictive... ...deployment, monitoring, and lifecycle management; implement testing/... ...and govern the end-to-end AI/ML optimization strategy—from architecture...
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