3 months ago
Toronto, CanadaSenior
Responsibilities
- Build and train production ML models for pricing, automation, and business-critical decision systems.
- Convert research prototypes into clean, testable, production-ready code and systems with researchers and analysts.
- Own model pipelines end-to-end, including data ingestion, training, validation, versioning, deployment, and monitoring.
- Design and evolve mission-critical services and APIs connecting ML systems to messy real-world operations.
- Build platforms for agentic research, automated retraining, experimentation, deployment, and monitoring.
- Address sparsity, data drift, model decay, and other challenges in volatile real-world markets.
- Use AI tools in daily work and help advance their application to ML engineering.
- Lead technical design reviews, mentor teammates, and improve engineering quality.
Requirements
- Senior-level or above experience shipping and operating production ML systems, ML-adjacent services, or data/ML platforms.
- Strong Python fundamentals and the ability to learn additional programming languages or tools.
- Proficiency in statistics and the ability to reason about distributions and real-world ML monitoring.
- Expertise across the ML lifecycle, including training, evaluation, deployment, monitoring, and iteration.
- Experience with associated tooling such as MLflow, Airflow, Spark, and Delta Lake.
- Ability to make and communicate architectural and technical tradeoffs across stakeholders.
- Based in or willing to relocate to Miami, Toronto, or Seattle.
- Preferred experience includes ML systems in pricing, forecasting, logistics, marketplaces, or risk.
- Preferred experience includes streaming and event-driven systems, Kafka, gRPC, Redis, or workflow engines.
- Interest in real estate or other messy, high-stakes domains with imperfect data.
Benefits
- The role is based in or requires relocation to Miami, Toronto, or Seattle.
- The interview process typically includes a recruiter screen, a technical deep dive, and two pairing-style technical reviews.
Tech Stack
Categories
About Opendoor
Opendoor builds a digital platform for buying and selling homes, offering instant cash offers to sellers and self-serve tools for buyers to tour and purchase. The company makes money by purchasing homes, reselling them, and providing related real estate services. Founded in 2014 and headquartered in San Francisco, Opendoor is a public company traded on NASDAQ (OPEN) and operates across many U.S. housing markets.