Position: ML Operations Engineer/Architect
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