Staff Machine Learning Engineer: Lead AI Systems & Growth

Unity Technologies; Mountain View (CA); On-site; USD 218,000 - 284,000; Full time

Benefits offered by this job

Comprehensive health insurance

Employee stock ownership

Competitive retirement plans

Generous vacation and personal days

Parental leave and family-care support

Job summary

Unity Technologies is building next-generation intelligence systems for gaming and AI-native teams. We are hiring a Staff Machine Learning Engineer to lead end-to-end architecture, pipelines, and models, scaling a cross-disciplinary team of engineers across engine, game, and ML domains.

You will own data ingestion, feature stores, model registry, evaluation, and serving, while shaping the roadmap with product teams and ensuring reproducibility, cost controls, and guardrails for agentic systems.

Qualifications

• Experience owning production ML systems end to end, from data to serving to business outcomes.
• Strong grounding in probabilistic prediction, calibration and backtesting of forecasts.
• Experience building LLM-based agent systems in production: orchestration, evaluation harnesses, prompt and model versioning.

Responsibilities

• Define and own the ML platform architecture (data ingestion, feature stores, model registry, evaluation, serving).
• Lead cross-disciplinary engineering efforts and mentor engineers across teams.
• Develop predictors for commercial outcomes and forecast market signals to inform decisions.
• Design online experiments with guardrails and build evaluation harnesses for agentic systems.

Skills

Production ML systems

Python

Team leadership

Cost control

Tools

BigQuery

Kafka

Postgres

ClickHouse

pgvector

Job description

Unity Technologies is building next-generation intelligence systems for gaming and AI-native teams. We are hiring a Staff Machine Learning Engineer to lead end-to-end architecture, pipelines, and models, scaling a cross-disciplinary team of engineers across engine, game, and ML domains.

You will own data ingestion, feature stores, model registry, evaluation, and serving, while shaping the roadmap with product teams and ensuring reproducibility, cost controls, and guardrails for agentic systems.