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Machine Learning Operations Architect
Remote, RemotePosition: ML Operations Engineer/Architect Location: Remote Duration: 6+ months contract We are looking for a highly motivated and experienced Machine Learning Operations Architect to assist with developing these next-generation AI/ML operational platforms. The role will require hands on experience with infrastructure automation, CI/CD pipelines, feature extraction/feature definition, data validation, model monitoring, and model lifecycle management. What You’ll be Doing • Creating a platform to automate every step of the ML Process from Data Prep, Model Building, Deployment, and Operations • Extracting data from a data store, cleaning the data, and preparing it for consumption • Constructing data pipelines to maintain the model • Monitor the model for performance and drift • Coding everything required to orchestrate multiple models together • Automating deployment through CI/CD environments • Creating and automating model workflows • Authoring dashboards to manage and monitor the end-to-end model lifecycle What your Background Looks Like • BS or MS (preferred) in Computer Science or a related field • 5+ years current practical experience developing production-quality applications in Python. • Strong software design and enterprise architecture skills, particularly with AWS services. • 3-5 years of experience with enterprise grade CI/CD pipeline deployment • 2-3 years of experience with large-scale production machine learning orchestration between multiple accounts. • Demonstrated Knowledge of Data ETL (Spark preferred – streaming and structured streaming), Analytics, ML Libraries (scikit-learn, XGBoost, MXNet, Tensorflow, R), ML Frameworks (Airflow, MLFlow, Kubeflow) • Solid grounding in statistics, probability theory, data modeling, machine learning algorithms and software development techniques and languages used to implement analytics solutions. • Proven capability of working with both technical and business stakeholders • Excellent written, oral communication, and analytical skills • Experience in neural networks/deep-learning techniques • Experience with modern software development practices and tools • Polyglot: can program effectively in a wide range of programming languages and frameworks • Ability to work in a fast paced environment and to be an outstanding team player • Ability to learn new frameworks and environments • Adept at asking for help when needed |