Technical Lead, ML Infrastructure Santa Clara, CA

Gatik; Santa Clara (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Gatik is seeking a hands-on technical leader for Scalable ML to set direction, architect data and training pipelines, and drive rigor in model evaluation. You will mentor engineers, write production-grade code, and align infrastructure with platform teams across ML and autonomy groups.

You’ll lead the design of robust data generation, versioning, and experiment tracking, ensuring reliable, scalable ML workflows and decisions that underpin safe autonomous freight operations.

Qualifications

• Bachelor’s degree in CS, EE, Robotics, or related field with 8+ years in industry, or Master’s with 6+ years and 2+ years in tech lead roles.
• Expert Python software engineering skills with production-grade code.
• Deep experience building end-to-end ML systems: data pipelines, training, eval, prod.
• Hands-on production experience with Ray; scalable ML workloads.
• Deep experience with PyTorch for large-scale training; distributed strategies.
• Experience designing and operating large-scale distributed systems and cloud infra for ML.

Responsibilities

• Set multi-quarter technical strategy for data generation, curation, orchestration, and training pipelines.
• Code from the ground up to shape the stack and enforce quality and reviews.
• Architect reproducible data pipelines with versioning and data contracts.
• Guide dataset quality and coverage for diverse driving scenarios.
• Design distributed training, inference, and evaluation pipelines on multi-tenant GPUs.

Skills

Python

Distributed ML

Leadership

System design

Cloud platforms

Education

Bachelor’s degree in Computer Science or related field

Master’s degree in CS or related field

Tools

PyTorch

Ray

SQL

Pandas

AWS/GCP

Job description

Gatik is in the business of autonomous freight, and that business is already on the road.

Every day, Gatik’s autonomous trucks move freight for Fortune 50 retailers, grocers and consumer brands across Texas, Arizona, Arkansas and Canada, connecting distribution centers and stores and keeping goods moving. At the heart of it all is the Gatik Driver™, our proprietary Level 4 autonomous driving system, powered by scalable, interpretable AI and engineered to deliver safe, reliable, high-frequency freight operations.

Gatik’s momentum is real. With more than $600 million in contracted revenue and $200 million raised in our August 2026 Series D round, Gatik has taken one of the toughest challenges in autonomous technology and turned it into a proven commercial business.

And the market is paying attention. In 2026, Gatik earned a place on Forbes' America's Best Startup Employers list, and the Inc. 5000 list of America's fastest-growing private companies. The Gatik Driver™ won an Edison Award for Advancements in Autonomous Driving, and Inc. named our Co-founder and Chief Engineer, Apeksha Kumavat, to its Female Founders 500 list.

There's a lot more road ahead, and some of the brightest, most driven minds in autonomous technology are building the next chapter at Gatik. We're taking on hard engineering problems, pushing the limits of what's possible and building on a commercial foundation that's already proven itself in the real world with some of the biggest companies in the world, like PepsiCo and Loblaw. If you're ambitious, love solving problems that matter and want to see your work make a real difference, you'll find plenty to get excited about here.

About the Team

Scaling our machine learning models with data and fast infrastructure is central to how Gatik’s autonomy stack keeps improving. The Scalable ML team builds the data generation, curation, orchestration, and distributed training infrastructure that lets our ML developers work efficiently with large volumes of real-world fleet data and simulated driving scenarios. The team sits at the intersection of ML Platform, Jobs Platform, Cloud Platform, and High Performance Computing, and partners closely with Gatik’s autonomy, simulation, safety, and data teams.

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.

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.

For the latest company news, visit the Gatik newsroom.

At Gatik, we connect people of extraordinary talent and experience to an opportunity to create a more resilient supply chain and contribute to our environment’s sustainability. We are diverse in our backgrounds and perspectives yet united by a bold vision and shared commitment to our values. Our culture emphasizes the importance of collaboration, respect and agility.

We at Gatik strive to create a diverse and inclusive environment where everyone feels they have opportunities to succeed and grow because we know that together we can do great things. We are committed to an inclusive and diverse team. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

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