A four-year degree in computer science or a related field and a strong program management background.
Overall 4+ years of experience in the technology industry with 2-3 years working on Machine Learning & Statistics projects.
Strong consulting skills and proven background of driving customer engagements in a professional services capacity
Experience leading agile development and engineering efforts from initial envisioning and epic construction to product deployment.
Strong demonstrated experience leading diverse teams through rapid development cycles and producing high-quality software products and services at scale.
Knowledge of Machine Learning pipelines - data ingestion, feature engineering, modeling, predicting, explaining, deploying and monitoring ML models.
Experience leading teams working with Python, or R languages and general software development skills (source code management, debugging, testing, deployment, etc.)
Knowledge of one or more toolkits such as sklearn, MXNet, Keras, Tensorflow, PyTorch, NLTK, OpenCV, spaCy, etc.
Knowledge and project-level experience with Azure, GCP and/or AWS.
Drive detailed-level design sessions and prioritize and organize work across releases, iterations, and sprints.
Report and analyze engagement outcomes and for continuous improvement and cycle-time reduction
What you’ll do:
Bring ML experiments from Notebooks to production. Deploy ML models under the constraints of scalability, correctness, and maintainability.
Collaborate with cross functional agile teams of machine learning engineers, data engineers, and others in building machine learning