Lead ML Engineer - Fully Remote Production Systems

Next Step Systems; San Francisco (CA); Remote; USD 160,000 - 190,000; Full time

Benefits offered by this job

Medical insurance

Dental

Vision

Savings plan

Paid time off

Job summary

Next Step Systems is seeking a Machine Learning Lead Engineer who owns the execution layer of our intelligence, turning research into reliable production ML systems. This 100% remote, work-from-home role covers data, training, evaluation, inference, and deployment and is hands-on with leadership responsibility.

Qualifications include ML production experience, strong software engineering fundamentals, and GPU-based workloads.

Qualifications

• ML experience is required.
• Experience shipping ML systems in production.
• Strong understanding of large-model training, fine-tuning, evaluation, and inference.
• Strong software engineering and systems fundamentals.
• Experience operating ML workloads at scale on GPUs.
• Independent problem solving with good technical judgment.
• High standards for correctness and reliability.

Responsibilities

• Own end-to-end ML systems from data to deployment.
• Build and evolve pipelines for training and fine-tuning large models.
• Design evaluation systems for capability, robustness, safety and performance.
• Architect high-performance inference systems optimizing latency and memory.
• Build data pipelines for real-world and synthetic training data.
• Establish production infrastructure for deploying, monitoring and improving models.
• Collaborate with research and application engineering to ship improvements.
• Make pragmatic trade-offs and iterate based on real-world results.

Skills

ML deployment

System design

Software engineering

Experimentation mindset

Independent problem solving

Tools

Python

PyTorch/JAX

GPU-based training

Job description

Next Step Systems is seeking a Machine Learning Lead Engineer who owns the execution layer of our intelligence, turning research into reliable production ML systems. This 100% remote, work-from-home role covers data, training, evaluation, inference, and deployment and is hands-on with leadership responsibility.

Qualifications include ML production experience, strong software engineering fundamentals, and GPU-based workloads.