Machine Learning Technical Lead, Work From Home
As Machine Learning Technical Lead, you own the execution layer of intelligence. You will translate research direction into reliable, scalable, production-grade ML systems. This role sits at the intersection of research, infrastructure, and product. You will be responsible for making models trainable, deployable, observable, and performant under real-world constraints. This position is 100% Remote.
Machine Learning Technical Lead 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
Machine Learning Technical Lead 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.
Machine Learning Technical Lead Qualifications:
- Experience building or shipping real Machine Learning systems used by people, not just demos.
- 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.
- You communicate 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.
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