$80K — $100K *
About the Role Teikametrics is looking for a Machine Learning Engineer to join a team under the Data Science directorate tasked with building a platform that supports the rapid construction and deployment of prediction and control services in the domain of E-commerce. Candidates should have an understanding of machine-learning and statistical modeling concepts paired with strong software engineering fundamentals. The Data Science team's predictive services are developed in Python on top of AWS Sagemaker, orchestrated by Airflow and backed by a data warehouse in Snowflake. Our back-end code emphasizes a ‘functional-first’ Scala stack with cats and fs2. The team's mandate is to design and build infrastructure that enables us to safely deploy solutions to the multi-agent, game-theoretic problems at the heart of decision-making in E-commerce. This entails model train/evaluate/serve lifecycle management, ML metadata storage and visibility, provisioning of separate environments for staging and integration testing, and task orchestration. The team will adopting existing solutions, like Kubeflow or AWS Sagemaker, where appropriate and fill in the rest. Qualified candidates should have: * 1+ years of experience working as a professional software developer. * Proficiency in Python with exposure to some subset of the Python ML ecosystem (numpy/scipy/pandas, Tensorflow, etc.). * Exposure to machine-learning model lifecycle; training, evaluation, serving. * Interest in deploying machine-learning models as scalable services. * Interest in "tool-making"; building features for developers that empower them and make them faster. * Passion for learning and growing as a developer. * Desire to work in a collaborative environment focusing on continuous learning; participating in tech talks, code review, and pair programming.
Valid through: 8/24/2020