Staff Machine Learning Engineer

Revecore-posted 2 months ago
Entry Level
1,001-5,000 employees
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As a Machine Learning Engineer at Revecore, you will use your expertise in machine learning, exploratory data analysis, and software engineering to enhance the productivity and efficiency of our underpayment business. You will work on projects with purpose, such as prioritizing claims based on expected recovery dollars and improving our claim-remit matching process. This is a modeling team that owns the model deployment process. You won’t be building dashboards or pivot tables. You won't just build POCs. Our team increases revenue and decreases costs: you will deploy your work and see the results as we increase our client hospitals' revenue.

  • Own end-to-end development, training, deployment, evaluation, and improvement of machine learning systems to rank claim opportunities.
  • Analyze and explore data to identify actionable opportunities from internal and 3rd party data.
  • Research, implement, and launch new model architectures that drive business impact.
  • Partner and collaborate with cross-functional teams of software engineers, data engineers, subject matter experts, product managers, and analysts to design and build practical solutions.
  • Implement cloud MLOps best practices to streamline the development, deployment, and maintenance of machine learning models.
  • Continuously measure the impact of the AI-enabled workflows on key business metrics and use these measurements to improve the machine learning models and workflows.
  • Learn from and teach your teammates. You will become the team’s expert in your specialization, and you will learn from experts in theirs.
  • A bachelor's degree in any data-centric field. Scientific thinking is a must.
  • Experience working in a similar role, with a focus on machine learning or data science.
  • Experience developing and deploying machine learning models in a production environment.
  • Strong experience with Python, including scikit-learn. TensorFlow or PyTorch is a plus.
  • Ability to wrangle data, perform exploratory data analysis, and draw insights from visualizations.
  • Intuition about data developed by doing statistics and/or research. Bonus points if you know the difference between MAR and MCAR, or can draw causal inferences from historical data.
  • Applied experience with contemporary natural language processing (NLP) techniques and tools (e.g., entity extraction, transformers, Hugging Face).
  • Experience with Spark.
  • Experience with operating ML pipelines in a cloud platform (e.g., AWS, GCP, Azure).
  • A Master's degree, Ph.D., or other experience demonstrating scientific thinking.
  • Comprehensive medical, dental, vision, and life insurance benefits from the start of your employment.
  • 12 paid holidays and flexible paid time off.
  • 401(k) contributions.
  • Employee Resource Groups that build community.
  • Career growth opportunities.
  • An excellent work/life balance.
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