Tech Lead - Scalable ML Infrastructure

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 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.