ML Platform Engineer: Feature Stores & Pipelines

Boerboel; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

An electronic trading firm is seeking a talented ML DevOps Engineer to design and implement a feature store, data lake, and MLOps pipelines. The successful candidate will contribute to a high-performance infrastructure handling extensive financial data, working with a team of passionate colleagues in London. Ideal applicants will have strong Python skills and experience with distributed computing frameworks, contributing to scalable ML workloads. Full-time position available with competitive opportunities for growth.

Qualifications

• Strong Python development skills and experience with data pipelines.
• Experience building MLOps pipelines at scale.
• Familiarity with data lake organization and serving large datasets.

Responsibilities

• Design and implement scalable infrastructure for time-series feature storage.
• Develop end-to-end workflows for data ingestion and model training.
• Deploy feature computation and model inference with required latency.

Skills

Strong Python engineering with focus on data pipelines

Experience with MLOps pipelines

Experience ingesting and organizing large datasets

Familiarity with Spark or similar frameworks

Tools

Parquet

Airflow

Dask

Spark

Job description

An electronic trading firm is seeking a talented ML DevOps Engineer to design and implement a feature store, data lake, and MLOps pipelines. The successful candidate will contribute to a high-performance infrastructure handling extensive financial data, working with a team of passionate colleagues in London. Ideal applicants will have strong Python skills and experience with distributed computing frameworks, contributing to scalable ML workloads. Full-time position available with competitive opportunities for growth.