Staff Software Engineer, ML Training Infrastructure

stackav; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

STACKAV is seeking a seasoned Platform Engineer to set the technical direction of a multi-tenant ML training platform. You will shape orchestration, training abstractions, and observability, spanning data prep through training, validation, and profiling for autonomous-vehicle related systems.

You will drive scalable infrastructure, lead cross-functional teams, and integrate profiling/optimization tools to accelerate model iteration while ensuring reliability and traceability across modeling

Qualifications

• Requires 6+ years building ML platforms and applications.
• Strong programming skills in Python and C++ or equivalent.
• Experience with ML/data platforms (Lance, PyTorch, Ray Data) or similar.
• Track record of building scalable, reliable infra with multiple modeling teams.
• Ability to explain tradeoffs and align cross-functional teams.
• Excellent analytical, problem-solving, and communication skills.

Responsibilities

• Set technical direction for orchestration, training abstractions, control-plane operations, observability, and performance tuning.
• Build end-to-end model pipelines: log processing, feature extraction, dataset schemas, storage, training, profiling.
• Investigate infrastructure performance and remove bottlenecks to speed up iteration.
• Provide reusable abstractions and tools to help ML engineers work independently.
• Integrate open-source tools for profiling and optimization; promote engineering best practices.
• Collaborate across platform, infrastructure, autonomy, and safety groups while balancing hands-on work with long-term direction.

Skills

Python

C++

ML platforms

Data platforms

Performance optimization

Cross-functional collaboration

Education

Bachelor’s or Master’s degree in CS/Engineering

Tools

Lance

PyTorch

Ray Data

Job description

Role overview

Set technical direction and build core infrastructure for a multi-tenant machine learning training platform. The work spans the AI development workflow, from data preparation and model configuration through training, validation, profiling, and acceleration, helping machine learning teams iterate more quickly and reliably on systems used in autonomous vehicles.

Responsibilities

• Design and evolve platform components for orchestration, training abstractions, control-plane operations, observability, and performance tuning.
• Build end-to-end model pipelines covering log processing, feature extraction, dataset schemas and storage, model configuration, training, and profiling.
• Investigate infrastructure performance and remove bottlenecks affecting training and iteration speed.
• Provide reusable abstractions and tools that help machine learning engineers work independently and efficiently.
• Integrate open-source tools for profiling and optimization, and encourage effective engineering practices across teams.
• Partner across platform, infrastructure, autonomy, and safety evaluation groups while balancing hands-on engineering with longer-term technical direction.

Requirements

• Bachelor’s or master’s degree in computer science, engineering, or a related field.
• At least six years of experience with machine learning platforms and machine learning applications.
• Strong programming skills in Python, C++, or an equivalent language.
• Experience with a machine learning or data platform such as Lance, PyTorch, or Ray Data, or comparable tools.
• Track record building scalable, reliable infrastructure with engineers across multiple modeling teams.
• Experience with model training, model optimization, or large-scale data processing, plus the ability to explain technical tradeoffs and build cross-functional alignment.
• Strong analytical, problem-solving, written, and verbal communication skills.

Nice to have

• Autonomous vehicle experience; modeling experience is also a plus.