Next Step Systems

Machine Learning Lead Engineer, Machine Learning (ML) Required, Work From Home

Next Step Systems San Francisco, California, United States · $160K–$190K/yr

Staffing and Recruiting · 2-10 employees

6 h ago
Remote machine-learning Senior (5-10 yrs) Full-time United States
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About the role

You will own the end-to-end machine learning systems, managing everything from data pipelines and training loops to inference and production deployment. You will also collaborate with research and application teams to translate model capabilities into scalable, high-performance product solutions.

What they look for

Machine Learning Python PyTorch JAX GPU-based training Inference systems Model deployment Data pipelines Software engineering Large model training Fine-tuning System architecture Latency optimization Model evaluation Production infrastructure

Requirements

Candidates must have professional experience building and shipping machine learning systems into production environments. Strong proficiency in Python, PyTorch/JAX, and GPU-based infrastructure is required, along with a solid foundation in software engineering.

Benefits

Medical insurance Dental Vision Savings plan options Paid time off

Full description

Job Description

Machine Learning Lead Engineer, Machine Learning (ML) Required, Work From Home

 

As Machine Learning Lead Engineer, you own the execution layer of our intelligence, turning research and model capabilities into reliable, scalable production systems.  You will work across the model lifecycle: data, training, evaluation, inference, and deployment.  This is a hands-on leadership role for someone who wants to operate at the intersection of research, systems, and product.  Machine Learning (ML) experience is required.  This position is 100% Remote.

 

MUST BE WILLING TO TAKE A 60 MINUTE CODING ASSESSMENT.

 

Machine Learning Lead Engineer Responsibilities:

 

- Own the end-to-end Machine Learning (ML) systems powering our company, from data and training to evaluation, inference, and deployment.

- Build and evolve training and fine-tuning pipelines for large models.

- Design evaluation systems that measure capability, robustness, safety, and real-world product performance.

- Architect high-performance inference systems, optimizing latency, GPU utilization, memory, cost, and reliability.

- Build data pipelines and systems for high-quality real-world and synthetic training data.

- Establish reliable production infrastructure for deploying, monitoring, and continuously improving models.

- Partner closely with research and application engineering to turn model capabilities into product improvements.

- Make pragmatic technical trade-offs and rapidly iterate based on real-world performance.

 

Outcomes

 

- Research and models reliably translate into production-ready solutions with clear performance and quality targets.

- ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.

- Production issues are detected, debugged, and resolved quickly, minimizing user impact.

- Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.

- Iterations on models and systems are measurable, safe, and improve user experience over time

Qualifications

Tech Stack:  Python, PyTorch/JAX, and GPU-based training and inference system.

 

Machine Learning Lead Engineer Qualifications:

 

- Machine Learning (ML) experience is required.

- Experience building and shipping Machine Learning (ML) systems used in production, not just research prototypes.

- Strong understanding of modern large-model training, fine-tuning, evaluation, and inference.

- Strong software engineering and systems fundamentals.

- Experience operating Machine Learning (ML) workloads at meaningful scale, particularly GPU-based systems.

- Strong technical judgment and the ability to navigate ambiguous problems independently.

- A bias toward experimentation, measurement, and shipping.

- High standards for correctness, reliability, and production quality.

 

Machine Learning Lead Engineer Ideal Experience:

 

- You have built or shipped real Machine Learning (ML) systems used by people, not just demos.

- You are comfortable working with large models and understanding their failure modes.

- You write strong, production-grade code and care about system correctness.

 

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

 

Keywords:  San Francisco CA Jobs, GPU, JAX, Machine Learning Lead Engineer, ML, Machine Learning, Python, PyTorch, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting

 

Looking to hire a Machine Learning Lead Engineer in San Francisco, CA or in other cities?  Our IT recruiting agencies and staffing companies can help.

 

We help companies that are looking to hire Machine Learning Lead Engineers for jobs in San Francisco, California and in other cities too.  Please contact our IT recruiting agencies and IT staffing companies today!

Additional Information

Please check out all of our jobs at www.nextstepsystems.com.

 

  • Compensation: USD 160000 - USD 190000 - yearly

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