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Senior Machine Learning Engineer

  • 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:

  • Design and build models, data pipelines and production-level machine learning (ML) infrastructure, using tools such as sklearn, TensorFlow, PyTorch, Kubernetes, Kubeflow Pipelines. Leverage your experience to drive best practices in ML systems and data engineering.
  • 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

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