Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company. We are seeking a staff ML engineer to design and evolve the large-scale offline platform, focusing on building reliable infrastructure for generating training datasets, orchestrating ML workflows, and enabling efficient, distributed model training at scale.
Requirements
- Strong experience building large-scale ML pipelines
- Experience working with distributed computing frameworks such as Ray, Spark, Flink and familiarity in the Ray ecosystem (Ray Data, Ray Train) for distributed data processing and model training
- Experience building infrastructure for training data generation, dataset preparation, or ML feature pipelines
- Deep experience designing and operating production-grade data pipelines
- Strong programming skills in Python and experience working with large-scale distributed workloads
- Experience with modern data infrastructure (data lakes, warehouses, orchestration systems, streaming platforms)
- Strong systems thinking, with the ability to reason about performance, scalability, reliability, and cost tradeoffs in distributed systems
- Proven ability to lead technical direction and influence architectural decisions across teams without formal authority
Benefits
- Comprehensive health, life, and disability insurance
- Commutue subsidy
- Employee stock ownership
- Competitive retirement/pension plans
- Generous vacation and personal days
- Support for new parents through leave and family-care programs
- Office food snacks
- Mental Health and Wellbeing programs and support
- Employee Resource Groups
- Global Employee Assistance Program
- Training and development programs
- Volunteering and donation matching program
