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Director, Machine Learning Engineer | Healthcare

Intelletec has partnered with an impact-driven healthcare company, looking to make quality care more accessible and affordable. They are seeking a Director, Machine Learning Engineer to join the team in Texas. 

 

You will own the MLOps CI/CD/CT strategy for deploying machine learning solutions at scale for current and future capabilities, whilst being passionate about building machine learning applications that ensure patients receive the medications they need.

 

Responsibilities:

 

  • Create the roadmap for next-generation data science workbench integrated with our new data mesh

  • Recruit top talent machine learning engineers to join your team.  Drive adoption of best-in-class capabilities, including Deep Learning, Natural Language Processing, and Next Best Action Recommenders.

  • Build, scale, deploy, and manage data science solutions in a multi-cloud environment to provide predictive insights that further the mission to improve care in every setting. 

  • Communicate strategy and results to technical and non-technical audiences; Develop and maintain strong relationships with key stakeholders, partners, and internal clients.

  • Manage business stakeholder relationships to drive action and value from data science insights

  • Partner with digital accelerators, universities, and consultants to accelerate innovation; Opportunities to co-author peer-reviewed publications and patent your AI/ML innovations

  • Solve problems from the business point of view, build and execute solid analytics work plans, gather and organize large and complex data assets.

 

Skills:

 

  • Bachelors or higher with relevant experience in machine learning; and software engineering, architecture, and design is required. The degree should be in computer science, applied mathematics, operation research or machine learning.

  • 10 years of relevant experience in machine learning; and software engineering, architecture, and design is required.

  • At least 3 years of management and mentorship experience with machine learning engineers/data scientists in business or scientific research settings.

  • Expert experience in one or more programming languages, Python plus Java, C/C++, …

  • Expert experience with MLOps, CI/CD/CT, scalable ML deployment (e.g. MLFlow, Kubeflow, Docker, Kubernetes)

  • Expert experience with cloud computing in Azure or GCP

  • Experience with distributed computing: (e.g. Databricks, Apache Spark, Hadoop…)

  • Experience with data pipelines, streaming architecture (Kafka), data engineering, creating feature stores, processing unstructured and structured data at scale.

  • Industry experience using TensorFlow and Pytorch to develop Representation Machine Learning Systems; e.g. Next-Best-Action, Recommendation systems; Deep Learning Neural Networks; Image understanding; Document classification and keyword extraction

  • Experience in core data science and predictive analytics methods: Statistics (t-tests, Poisson process), Segmentation and clustering techniques, predictive modeling: e.g. regression, classification, Time Series analysis: e.g. ARIMA, Traditional machine learning methods: e.g. Random Forest, ensemble model techniques, Optimization: e.g. linear programming

 

Perks:

  • Competitive base salaries and bonus 

  • Paid parental leave

  • Wellness rebates

  • 401k