Technical Lead, ML Infrastructure

About the Role

We're looking for a hands-on technical leader to set the direction for Scalable ML and build alongside the team. You'll own the architecture for how fleet and simulation data becomes training and evaluation sets, how models train and evaluate at scale, and how release decisions get backed by rigorous metrics. You'll spend a significant share of your time designing systems, writing production code, and reviewing critical changes, while also leading a team of engineers and serving as the technical bridge to the platform teams that Scalable ML depends on and shapes.

What You'll Do

• Set the technical direction. Define and own the multi-quarter technical strategy for data generation, curation, orchestration, and distributed training, including where it depends on or shapes the roadmaps of ML Platform, Jobs Platform, Cloud Platform, and HPC.
• Lead from the code. Design and build the hardest parts of the stack yourself, prototype new approaches, and set the standard for code quality, testing, type checking, and review through your own work.
• Architect scalable data pipelines. Own the design of reproducible pipelines that discover, label, and organize driving scenarios from Gatik's fleet and simulation, with versioning, provenance, well-designed train/validation/holdout splits, and clear data contracts.
• Drive dataset quality. Guide how the team builds balanced training and evaluation sets that cover the scenarios our trucks encounter across routes, weather, and traffic conditions, and use coverage and label-quality analysis to shape dataset and model priorities.
• Scale training and evaluation. Lead the design of distributed training, inference, and evaluation pipelines with robust data loading, checkpointing, and experiment tracking on multi-tenant GPU clusters.
• Set the MLOps standard. Drive model artifact management, experiment tracking, and automated model testing and deployment at a standard other teams across Gatik adopt.
• Own the metrics and the rigor. Define how model and release metrics (precision, recall, F1, ROC AUC, calibration, and task-specific metrics) are implemented and validated, and make sure experiments, baselines, ablations, and uncertainty estimates hold up to the bar that safety-critical release decisions demand.
• Lead and grow the team. Break down ambiguous problems into well-scoped work, guide technical decisions, mentor engineers through design and code review, and help the team grow its skills in scalable ML infrastructure.
• Resolve cross-team tradeoffs. Represent Scalable ML in architecture and planning discussions, and work with peer leads to resolve tradeoffs on shared infrastructure such as GPU scheduling and quota, job orchestration, storage, and compute cost.
• Own reliability. Hold the team's systems to a high reliability bar, and lead how incidents, including those that cross team boundaries, get root-caused, fixed, and prevented.

What You'll Need to Succeed

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field and 8+ years of relevant industry experience (or a Master's degree and 6+ years), including 2+ years as a technical lead, Staff engineer, or similar role guiding other engineers.
• Expert Python software engineering skills, and a track record of still writing and shipping production-quality, high-performance code as a leader.
• Deep experience building end-to-end ML systems, from data pipelines and dataset curation through training, evaluation, and production, using tools such as SQL, pandas, PyTorch, or scikit-learn.
• Hands-on production experience with Ray (Ray Core, Ray Data, Ray Train, and/or Ray Tune), including running and debugging Ray workloads at scale.
• Deep experience with PyTorch and PyTorch Lightning for large-scale training, including distributed strategies such as DDP or FSDP, mixed precision, and checkpointing.
• Extensive experience designing and operating large-scale distributed systems and cloud infrastructure for ML, including shared-compute environments with GPU scheduling and quota, job orchestration, and multi-tenant clusters.
• Solid grounding in statistics and experimental design, including choosing evaluation strategies, metrics, and thresholds that support real-world decisions.
• A track record of setting technical direction across a team or multiple teams, and delivering complex, cross-team initiatives from conception to production.
• Demonstrated ability to influence and align peer teams and leaders without direct authority.
• Clear communication and the ability to mentor engineers and work effectively across software, ML, and autonomy teams.

Salary Range $180,000 - $260,000

More about Gatik

Founded in 2017, Gatik has grown into a commercial force in autonomous freight, operating trucks daily in live customer networks across the United States and Canada. We're headquartered in Santa Clara, California, but our impact is felt on the roads and in the supply chains that keep essential goods moving for some of the biggest companies in North America.

Our trucks do some of the most demanding work in freight, running high-frequency, time-sensitive routes between distribution centers and stores, where reliability matters every single day. For our customers, that means more capacity, better service and products arriving where they need to be, when they need to be there.

Behind it all is AI-first technology built from the ground up for autonomous trucking, capable of navigating highways and surface streets and tackling the complexity of real-world logistics at scale.

Visit Gatik for more company information and Careers at Gatik for more open roles.

Notable News

For the latest company news, visit the Gatik newsroom.

Recent media coverage

• TechCrunch: Self-driving truck startup Gatik raises $200M following PepsiCo deal
• Reuters: Gatik secures $200 million in funding as autonomous freight market accelerates
• Bloomberg: Driverless Trucks Can Save Lives on America's Roads
• PepsiCo website: PepsiCo and Gatik announce multi-year agreement to deploy autonomous freight in North America
• Wall Street Journal: Driverless Trucks Are Here - and They're Delivering Bags of Doritos
• CBS News: Pepsi deploys self-driving delivery trucks
• Bloomberg: Autonomous Trucking Firm Gatik Inks Contracts Worth $600 Million
• Forbes: Hundreds' Of Gatik Robot Delivery Trucks Headed For U.S. Roads
• CNBC-TV18: No more test runs: Gatik says driverless trucks are now a real, money-making business
• Forbes: Gatik And Loblaw Announce Largest Commercial Deployment Of AV Trucks