2 days ago
Santa Clara, CA, USASenior / Staff+
H1B sponsor
Base Salary
$180k - $260k/yr
Responsibilities
- Design and maintain reproducible pipelines for discovering, labeling, organizing, versioning, and splitting fleet and simulation driving scenarios.
- Curate balanced training and evaluation datasets and analyze coverage, composition, and label quality.
- Build distributed training, inference, evaluation, data-loading, checkpointing, and experiment-tracking infrastructure for multi-tenant GPU clusters.
- Implement model artifact management, experiment tracking, automated model testing, and deployment practices.
- Define and validate model and release metrics, quantify uncertainty, and conduct baselines, ablations, and holdout experiments.
- Develop dashboards and services for comparing software versions, exploring scenario-level results, visualizing model outputs, and collecting reviewer feedback.
- Partner with platform and HPC teams on GPU scheduling, quota, job orchestration, storage, and compute-cost improvements.
- Improve interfaces, testing, type checking, CI, incident prevention, and cross-team reliability.
- At Staff level, define multi-quarter technical strategy, participate in architecture discussions, and mentor engineers across the team.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field and 5+ years of relevant industry experience, or a master’s degree and 3+ years of experience.
- Staff candidates typically have 8+ years of experience, including time setting technical direction beyond a single team.
- Strong Python software engineering skills for building modular, maintainable, high-performance, and well-tested systems.
- Experience building end-to-end ML systems covering data pipelines, dataset curation, training, evaluation, and production.
- Hands-on production experience with Ray workloads at scale, including Ray Core, Ray Data, Ray Train, and/or Ray Tune.
- Deep PyTorch and PyTorch Lightning experience for large-scale training, including DDP or FSDP, mixed precision, and checkpointing.
- Experience operating scalable ML infrastructure, distributed jobs, experiment tracking, model serving, or distributed training and evaluation pipelines.
- Familiarity with shared-compute environments, GPU scheduling and quota, job orchestration, and multi-tenant clusters.
- Solid knowledge of statistics and experimental design, including evaluation strategies, metrics, and decision thresholds.
- Clear communication and effective collaboration across software, ML, and autonomy teams.
Benefits
- The role is part of a collaborative, diverse, and inclusive environment focused on autonomous freight and supply-chain sustainability.
- Gatik emphasizes opportunities for talent to succeed and grow, with collaboration, respect, and agility as cultural values.
Categories
Data EngineeringML Engineering
About Gatik AI
Gatik AI builds and operates autonomous middle‑mile trucking networks for retailers and consumer brands, delivered as a transportation‑as‑a‑service offering. Its Level 4, Class 3–7 trucks move B2B freight on short‑haul, repeatable routes, with commercial deployments in Texas, Arkansas, and Ontario, including a fully driverless service launched with Walmart in 2021. Founded in 2017 and headquartered in Santa Clara, it integrates software and hardware to run driverless deliveries between warehouses and stores.