Machine Learning Engineer or Applied Data Scientist
Role details
Job location
Tech stack
Job description
idea will come from the data. Sometimes it will come from the business. This is a high-ownership role for someone comfortable working across data, product, and engineering. You should be able to frame ambiguous problems, explore messy data, build models or heuristics, integrate with production systems, measure outcomes, and iterate quickly. We are not looking for someone who waits for perfect specs or over-polishes a solution before proving it matters. Identify high-value opportunities from product, customer, and operational data Identify high-value opportunities from product, customer, and operational data Own end-to-end execution across data exploration, modeling, experimentation, backend integration, and productization Help shape how GitKraken uses AI and data to improve developer workflows, team velocity, and product experience Python (for data/ML execution), alongside Go and TypeScript across our core product and backend environments Data & Infrastructure: Snowflake for data
Requirements
warehousing, AWS for cloud infrastructure, and Datadog for monitoring and observability Deep experience in machine learning, applied AI, or a similarly hands-on product data role at a Senior level A track record of shipping data or ML-powered capabilities into real products or operational workflows You've built and shipped data or ML-powered features, not just analyses Excellence - Competitive compensation with annual performance-based pay increases Balance - Versátil Paid-Time-Off Policy & paid company holidays (chosen by our employees) Health - Health, dental, and vision insurance with competitive employer cost-sharing Headquarters - Modern, fully equipped offices designed to maximize productivity in a hybrid environment Future - 401(k) retirement plan plus company matching