At Commence, we’re the start of a new age of data-centric transformation, elevating health outcomes and powering better, more efficient process to program and patient health. We combine quality data-driven solutions that fuel answers, technology that advances performance, and clinical expertise that builds trust to create a more efficient path to quality care. 

With human-centered, healthcare-relevant, and value-based solutions, we create new possibilities with data. We provide proof beyond the concept and performance beyond the scope with a focus on efficiencies that transform the lives of those we serve. With a culture driven by purpose, straightforward communication and clinical domain expertise, Commence cuts straight to better care. 

The Senior Machine Learning Engineer will build, optimize, and scale ML models that unlock insights across large, complex healthcare and government datasets. This position will work on distributed systems, leverage AWS ML services, and drive innovation in data science applications. 

• Design, implement, and optimize ML models for predictive analytics, classification, and anomaly detection.
• Work with large datasets and apply distributed computing techniques to improve performance.
• Deploy and scale ML models in cloud environments (AWS preferred).
• Partner with Data Engineers and Product teams to translate business needs into scalable ML solutions.
• Stay current with emerging techniques and tools, integrating them into production workflows.
• Strong programming proficiency in Python, with experience in ML libraries. 
• Solid understanding of machine learning algorithms, statistical methods, and when to apply different approaches.
• Experience with data manipulation and analysis tools. 
• Familiarity with cloud platforms (AWS particularly) and their ML services.
• Understanding of software engineering best practices, including testing, code review, and documentation.
• Ability to collaborate with cross-functional teams (product, engineering, business stakeholders).
• Ability to coach and mentor junior ML engineers on techniques and best practices, and optionally lead a small team.
• Strong communication skills to explain technical concepts to non-technical audiences.
• Problem-solving mindset and ability to work independently.

Qualifications

• 5+ years of experience in Machine Learning or related fields
• Expertise with distributed computing, big data frameworks, and performance optimization.
• Proven track record of taking ML models from research/prototype to production
• Experience working with large datasets and distributed computing when necessary
• Background in feature engineering, model selection, and performance optimization
• Understanding of data engineering principles and ETL processes
• Experience with A/B testing and experimentation frameworks
• Knowledge of model interpretability and bias detection techniques
• Familiarity with different types of ML problems (supervised, unsupervised, reinforcement learning)
• Familiarity with Databricks ML Flow is a plus.

Work Environment/Physical Demands

The work environment and physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

This is an office position. While performing the duties of this job, the employee regularly works in a climate-controlled environment. Candidates must be able to sit, read, work on a computer, and watch a computer screen for extended periods of time. Occasionally required to stand, walk, use hands and fingers, kneel or crouch.

Commence.AI is committed to providing equal employment opportunities to all applicants, including individuals with disabilities. If you require a reasonable accommodation to participate in the application process due to a disability, please contact Human Resources at (757) 306-4920 or hr@commence.ai.

Please note that unless you are requesting an accommodation, all applications must be submitted through our online application system.