Senior Machine Learning Engineer

Salary: $145,000 - 247,000 per year Requirements:

• Bachelors or Masters degree in Mathematics, Computer Science, Data Science, Statistics, or a related quantitative field, or equivalent practical experience
• 4–6 years of hands-on professional experience developing, evaluating, and deploying machine learning models in production
• Proficiency in Python, SQL, and Unix-based development environments
• Experience building, testing, and maintaining production-grade machine learning services and workflows
• Knowledge of machine learning fundamentals, statistical methods, model evaluation, and software engineering best practices
• Familiarity with natural language processing, computer vision, or other applied machine learning techniques
• Strong written and verbal communication skills for technical and non-technical audiences
• Experience with deep learning, complex neural network architectures, training or fine-tuning large language and generative AI models, or cloud platforms such as AWS and technologies including Kubernetes, Kubeflow, or EKS is helpful

• Identify healthcare product and business opportunities for machine learning and assess suitable approaches
• Design and develop machine learning models and production services for client-facing and internal applications
• Build scalable data pipelines, feature engineering workflows, and training datasets from structured and unstructured data
• Deploy and maintain production machine learning services using cloud infrastructure and MLOps practices
• Test and validate statistics, models, code, and production workflows to promote quality and reliability
• Apply and contribute to best practices for modeling, coding, architecture, and statistical methods
• Collaborate with technical and non-technical colleagues to define requirements, communicate findings, and deliver solutions
• Develop internal tools, reusable frameworks, and team standards to improve data science work
• Use AI tools to support experimentation, coding, analysis, and workflow efficiency, reviewing outputs carefully and exercising sound technical judgment
• Monitor model and service performance and improve solutions based on operational insights, evolving requirements, and business impact
• Support exploratory analyses, proofs of concept, and prototypes for emerging machine learning opportunities
• Work with platform and infrastructure teams to improve tooling for model training, deployment, observability, and reproducibility
• Help establish practices for experiment tracking, model versioning, feature management, and CI/CD
• Prepare technical summaries, recommendations, and presentations for stakeholders with varied technical backgrounds
• Evaluate tools, frameworks, and methodologies relevant to machine learning engineering, data science, and generative AI
• Participate in incident analysis and remediation for machine learning-enabled systems
• Share technical guidance and knowledge with peers through collaboration, feedback, and documentation
• Contribute to roadmap planning, estimation, and prioritization for machine learning and data science initiatives

• AI
• AWS
• CI/CD
• Cloud
• Computer Vision
• Fine-tuning
• Support
• Kubeflow
• Kubernetes
• Machine Learning
• MLOps
• Model Training
• Network
• Python
• SQL
• Unix
• Spark
• Web

More:

We are partnering with hackajob to recruit a Senior Machine Learning Engineer for athenahealth. Based in Boston, Massachusetts, the role follows a hybrid work model and reports to the Data Science Manager. Our Data Science team works on the athenaClinicals product within the athenaOne platform, partnering with product, engineering, and platform teams to apply machine learning and advanced analytics to healthcare workflows. Teams typically work in scrum groups of 2–4 and collaborate across technical and non-technical disciplines to deliver practical outcomes. Our vision is to simplify healthcare and support accessible, high-quality, sustainable care through technology and expert services. We value inclusion, accountability, and support, and are committed to diversity, equity, and inclusion. Compensation is $145,000–$247,000 in base salary, with pay determined by relevant factors; eligible employees may also receive annual bonuses, variable compensation, and equity. Benefits include health and financial coverage, commuter support, employee assistance and tuition programs, employee resource groups, collaborative workspaces, flexible work arrangements, and company events.

last updated 42 week of 2026