Technical Lead, AI Platform & ML Systems

Paraform; San Francisco (CA); On-site; USD 240,000 - 340,000; Full time

Job summary

Paraform is building the next generation AI recruiting marketplace. We are scaling our AI Platform with a technical leader who will own the ML stack, from data design to production ranking and agentic workflows.

You will manage a pod of applied AI and ML engineers while staying deeply involved in core ML work, delivering high-quality models and production-grade systems. You will drive evaluation rigor, optimize cost and latency, and partner with product and data science to maximize match quality

Qualifications

• Staff-level depth in ML or applied AI and ability to lead technical work.
• 1+ years managing or tech-leading engineers (TL/M) or 4+ years setting technical direction across multiple teams (Technical Director).
• Experience shipping production ML/LLM systems used at scale (retrieval, ranking, or related).
• Ability to measure model quality by business outcomes, not just offline benchmarks.
• Data-fluent: able to run SQL queries and sanity-check experiment readouts.
• AI fluency as a baseline, leveraging tools to boost team effectiveness.
• Ability to write operating norms, decision docs, and postmortems.

Responsibilities

• Hire, coach, and level a pod of applied AI and ML engineers.
• Own core ML work: data/labeling, feature design, model selection, training, and fine-tuning.
• Tackle hard modeling problems and ship fixes personally.
• Lead matching, ranking, and marketplace-centric ML efforts.
• Develop agentic, LL-powered workflows and ensure reliability and safety.
• Define evaluation frameworks to measure quality and business impact.
• Balance tool use and traditional ML for cost/latency efficiency.
• Translate business goals into quarterly team plans and ship them.

Skills

Staff-level ML

Team leadership

Production ML

Eval-driven

Data fluency

Job description

Paraform is building the next generation AI recruiting marketplace. We are scaling our AI Platform with a technical leader who will own the ML stack, from data design to production ranking and agentic workflows.

You will manage a pod of applied AI and ML engineers while staying deeply involved in core ML work, delivering high-quality models and production-grade systems. You will drive evaluation rigor, optimize cost and latency, and partner with product and data science to maximize match quality