About the role
What will you do at Ginas Tech Jobs?
Job Description
Staff Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home
As the Staff Machine Learning Engineer, you own the execution layer of intelligence. You translate research direction into reliable, scalable, production-grade Machine Learning (ML) systems. This role sits at the intersection of research, infrastructure, and product.
You are responsible for making models trainable, deployable, observable, and performant under real-world constraints. This position is 100% Remote.
Staff Machine Learning Engineer
Responsibilities
- - Own end-to-end Machine Learning (ML) system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
- - Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- - Architect and operate scalable inference systems, balancing latency, cost, and reliability.
- - Design and maintain data systems for high-quality synthetic and real-world training data.
- - Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
- - Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- - Collaborate closely with application engineering to integrate Machine Learning (ML) systems cleanly into backend, mobile, and desktop products.
- - Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
- - Work under real production constraints: latency, cost, reliability, and safety
- Staff Machine Learning Engineer Outcomes
- - Research and models reliably translate into production-ready solutions with clear performance and quality targets.
- - Machine Learning (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 Machine Learning (ML) work with minimal friction.
- - Iterations on models and systems are measurable, safe, and improve user experience over time.
Qualifications
- Staff Machine Learning Engineer
Qualifications
- - Experience building or shipping real Machine Learning (ML) systems used by people, not just demos.
- - Artificial Intelligence (AI) experience required.
- - Experience working with large models and understanding their failure modes.
- - Experience writing strong, production-grade code.
- - You are self-directed, pragmatic, and take full ownership of outcomes.
- - Experience communicating clearly and collaborate well in small, high-trust teams.
- - Tech Stack: GPU-based training and inference system, JAX, Python, and PyTorch.
Benefits
include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Staff Machine Learning Engineer, Data Pipelines, DPO, GPU, JAX, LoRA, Machine Learning Engineer, ML, Machine Learning, Python, PyTorch, QLoRA, SFT, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
Looking to hire a Staff Machine Learning 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 Staff Machine Learning 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.ginastechjobs.com.
Compensation
USD 150000 - USD 170000 - yearly
Which skills does this role require?
Make your next move
Build a shortlist and prepare
Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.
- Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
- Machine learning jobsCompare current openings and review what to look for in this role.
- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
Other roles to compare
Review the responsibilities and requirements before adding an opening to your shortlist.
Staff AI Engineer - Personalization, Brand, Communications Tech
American Express · New York, New York, United States
Staff Integration and AI Engineer (Order-to-Cash)
DDN · New York, New York, United States
Sr. Applied AI Engineer
phData · United States
Gen AI Engineer -Dallas, TX
Photon · Dallas, Texas, United States
AI Engineer 3 (AI Foundations)
Capital One · San Jose, California, United States
AI and ML Engineer
Booz Allen Hamilton · Lorton, Virginia, United States
Role information can change. Confirm current details on the original application page.