<link id='css--app'rel="stylesheet" href="/dist/css/app.min.css"> Opportunities – Trilogy

Opportunities

Machine Learning Engineer at AdaptiLab
Seattle, WA, US

About the role

Machine learning is core to our business, driving everything from our interview generation to our candidate ranking system. We're looking for a talented, experienced ML engineer to help us scale quickly, smartly and nimbly. This role offers a unique opportunity to join an amazing team and grow your career as AdaptiLab scales.


Responsibilities:

-Build machine learning products that help drive our business
-Make thoughtful architectural decisions with limited information translating business requirements into machine learning products
-Communicate decision rationales, formulating project plans and delivering results
-Automating model comparison and feature selection to optimize performance
-Shipping code to our staging and production environments multiple times a day
-Building data pipelines that allow us to improve our machine learning products and services
-Design and deploy efficient data services and stores

Who we're looking for:

-You have 3+ years experience leveraging machine learning to solve complex business problems
-You’re adaptable: You thrive in a fast-paced, ever-changing environment, and understand that the right solution and the perfect solution rarely coincide in startups
-Excited about AdaptiLab's mission of helping companies adopt Machine Learning technology
-Bonus: Masters or PhD in computer science or other STEM degree

You have some experience with:

-Python and SQL (Both required)
-Designing and deploying scalable production machine learning products
-Machine learning algorithms (Neural networks, gradient boosting) and model evaluation (cross validation, bias-variance trade-off)
-Architecting relational databases (PostgreSQL), NoSQL databases (MongoDB), and data warehouses
-Git and GitHub; software development workflows
-Managing deployment & operation of cloud services (AWS, Azure etc.)
-Big data tools (Kafka, Spark, HDFS)
-Bonus: Early-stage startup experience, especially joining at the seed or Series A stage and scaling a technical product