Staff Software Engineer, ML Training Infrastructure

About the Role:

Responsibilities:

• Design & evolve high-performance training platform components including orchestration, training abstractions, control plane, observability and performance tuning.
• Deliver end-to-end ML model pipelines across logs processing, feature extraction, dataset schema design/storage, model configuration management, model training, and profiling/acceleration workflows.
• Analyze training infrastructure performance to identify and resolve performance bottlenecks
• Evangelize system abstractions and tooling that enable MLEs to rapidly iterate on models.
• Incorporate OSS tools to enable ML engineers self-sufficiently profile and optimize their workflows
• Promote Engineering Excellence: Maintain a high bar for engineering excellence in their own work but also set a culture of engineering excellence within the team.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of experience with ML Platforms and building ML-based applications (modeling experience is a bonus).
• Strong programming skills in Python, C++ or equivalent.
• Prior experience with Lance, PyTorch, Ray Data or equivalent technologies.
• Proven track record of building scalable, reliable infra in a fast-paced environment while working with MLEs across multiple modeling teams.
• A deep understanding of design tradeoffs and ability to articulate those tradeoffs to build alignment across XFN teams.
• Experience with model training, model optimization, or large-scale data processing pipelines.
• Autonomous vehicles (AV) experience is a bonus.
• Strong analytical and problem-solving skills.
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
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