Senior Machine Learning Engineer

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., 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 and AIOps 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 be the team’s expert in your specialization, and you will learn from experts in theirs. Own a workstream. You’ll be the technical lead for the workstream, partnering with others to deliver. You’ll also work on other projects, but this workstream will be one of your key successes.

An urge to question assumptions, and to get it right (or at least good enough) even if your first idea is wrong. A commitment to collaborate, rather than go off in a corner only to appear when you need to submit a pull request. 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.

It would also be great if you have: Intuition about data developed by doing statistics and/or research. 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.

Pulled from the full job description

• Paid training
• 401(k)
• Health insurance
• 401(k) matching
• Paid time off
• Vision insurance
• Dental insurance

Full job description

Start your next chapter at Revecore! For over 25 years, we’ve been at the forefront of specialized claims management, helping healthcare providers serve more patients by helping them recover more revenue. We’re powered by people, driven by technology, and dedicated to our clients and employees. If you’re looking for a collaborative and diverse culture with a great work/life balance, look no further.

Revecore Perks:

• We offer paid training and incentive plans

• Our medical, dental, vision, and life insurance benefits are available from the first day of employment

• We enjoy excellent work/life balance

• Our Employee Resource Groups build community and foster a culture of belonging and inclusion

• We match 401(k) contributions

• We offer career growth opportunities

• We celebrate 12 paid holidays and generous paid time off, 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.

Work at Home Requirements: A quiet, distraction-free environment to work from in your home. A secure home internet connection with speeds >20 Mbps for downloads and >10 Mbps for uploads is required. The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive.