Ginas Tech Jobs
Machine Learning Technical Lead - Artificial Intelligence, AI, Required, Work From Home
Full-Time
$190k - $225k/yr
Senior
San Francisco, CA, USA
Remote
Remote role; candidates must reside in the United States.
About the job
Requirements
- Experience building or shipping real Machine Learning 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.
- Self-directed, pragmatic, and takes full ownership of outcomes.
- Clear communication and collaboration in small, high-trust teams.
- Tech Stack: GPU-based training and inference system, JAX, Python, and PyTorch.
Responsibilities
- Own end-to-end 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 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
- 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.
Desired Qualifications
- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- Experience with GPU optimization, memory efficiency, latency reduction, and scaling policies.