Odyssey is seeking a data engineer to own their ML/data platform, which involves a mixture of infrastructure, tooling, and data pipelines.
The role will enable researchers to efficiently work with multimodal data, conduct experiments, and move models to production.
The position offers significant autonomy in technical decisions and opportunities for growth into a technical leadership role.
Responsibilities include designing and implementing scalable data pipelines, collaborating with ML researchers, making architectural decisions, and improving Kubernetes-based infrastructure.
A typical week involves designing scalable data pipelines, optimizing data preprocessing, and improving data platform infrastructure.
Requirements:
Candidates must have 5+ years of software engineering experience, particularly in data platforms.
Strong Python development and system design expertise is required.
Deep experience with data pipeline development and ETL processes is essential.
Production Kubernetes experience and container orchestration expertise are necessary.
Hands-on experience with data-oriented ML infrastructure tools, such as experiment tracking and feature stores, is required.
Proficiency with cloud platforms like AWS, GCP, or Azure is needed.
Experience with data versioning and experiment tracking systems is important.
A solid understanding of ML workflows and researcher needs is required.
Benefits:
The position offers the opportunity to help build the data platform engineering team as the company scales.
Employees will have the chance to define the technical strategy for data platform and infrastructure.
There are opportunities to establish partnerships with data platform framework open source projects and vendors.
The role allows for shaping the technical hiring strategy and engaging with the broader data and ML infrastructure community.
