Job Title: Machine Learning engineer (10+ Year) Duration: 6-12+ Months Location: Remote. Likely working EST hours so preferring them to live in EST or CST time We are looking for more ML Engineering profiles who have experience in Python, API (flask, Fast API), microservices, Kubernetes, Docker, good enough knowledge of data science, and model production Candidate should have Google Colab open on their system, and we will test on data analysis, OOP, and model serving. We expect candidate to write their code i.e., no copy paste. We are okay if candidate wants to google syntax and check the documentation, but no Gen AI tools. • Core skills: microservices, python • Nice to have data bricks or big data analysis • Industry-- retail is helpful but not 100% required • Ideally will have some background knowledge for their tech stack-- re-building their ML Platform/Server infrastructure • Need to be able to assist with a more seamless transition Feedback on our candidates 1. Candidate’s experience is quite data science focused. We are looking for more ML Engineering skills. 1. Candidate’s experience doesn’t seem focused on technical skills and ML engineering either. 1. Candidate’s experience is too varied without much focus on ML engineering either. (Why might someone want to work here?) • Machine Learning Engineer • Overlaps-- combination of data scientist and Machine Learning Engineer • Level 3-- a candidate with 0-1 year with a master’s degree or more experience also • Day to Day • Primarily responsibilities maintain pipelines • Build model servicing endpoints • Product use cases or building use cases • If the data scientist wants to build a new model which would recommend a specific set of products-- how to take that requirement and implement a model serving and implement to the product team • Get a requirement from the product team (which is in house exploratory tasks) • If tomorrow, they see any data relative issues, can jump into the data, and get into that • Core skills: microservices, python • Nice to have data bricks or big data analysis • Industry-- retail is helpful but not 100% required • Soft skills: • Communication is important • Work with the Product team which is also in residence with the Data Scientist-- reach out to the product and then the ML Engineer comes in wearing the red cape and productionizing it and making the idea into a reality • Works with the platform team-- manage the ML platform • Will be working with them-- the platform/networking/nitty gritty of tech infrastructure will provide the service for this-- will convey stuff back • Ideally will have some background knowledge for their tech stack-- re-building their ML Platform/Server infrastructure • Need to be able to assist with a more seamless transition • Definitely need someone who can pick up a new skill fast • Also work as a liaison between the 2 teams and the ML Engineer