Senior AI/ML Engineer, epocrates
$124,000–$210,000 year
Hybrid · Boston, Massachusetts, United States or Austin, Texas, United States
Job Summary
Senior AI/ML Engineer responsible for end-to-end AI/ML projects, building production-grade pipelines that support high-volume workloads, collaborating with cross-functional teams to deploy and monitor scalable AI/ML solutions for healthcare products, and advancing responsible AI practices including fairness, transparency, and data privacy. The role involves research-to-production work, deployment governance, monitoring, and ensuring maintainability of models in production with an emphasis on practical engineering, scalability, and collaboration across engineering, product, and clinical stakeholders.
Required Qualifications
- Bachelor’s Degree in Data Science, Mathematics, Statistics, Operations Research, Computer Science/Engineering, or a related technical field
- 4–6 years of professional experience in software engineering, with exposure to software development, data science, or AI/ML work
- Experience contributing to AI/ML projects across the model lifecycle, including research, prototyping, deployment, or monitoring
- Foundational knowledge of classical AI/ML algorithms, deep learning, Natural Language Understanding and Processing, and Generative AI concepts
- Familiarity with large language models, GPT, BERT, LangChain, and LangGraph concepts and applications
- Experience or exposure to building and deploying AI/ML systems in AWS
- Proficiency in Python and working knowledge of a JVM language/service
- Proficiency in working with SQL and non-SQL data
- Experience with at least one major ML framework, such as TensorFlow or PyTorch
- Exposure to MLOps and machine learning workflow orchestration; experience with AWS SageMaker is a plus
- Strong communication and interpersonal skills, with the ability to work effectively across technical and non-technical partners
- Interest in staying current with AI research and applying new techniques responsibly in production
- Healthcare technology experience is a plus, but not required
Desired Qualifications
- Bachelor’s Degree in Data Science, Mathematics, Statistics, Operations Research, Computer Science/Engineering, or a related technical field
- 4–6 years of professional experience in software engineering, with exposure to software development, data science, or AI/ML work
- Experience contributing to AI/ML projects across the model lifecycle, including research, prototyping, deployment, or monitoring
- Foundational knowledge of classical AI/ML algorithms, deep learning, Natural Language Understanding and Processing, and Generative AI concepts
- Familiarity with large language models, GPT, BERT, LangChain, and LangGraph concepts and applications
- Experience or exposure to building and deploying AI/ML systems in AWS
- Proficiency in Python and working knowledge of a JVM language/service
- Proficiency in working with SQL and non-SQL data
- Experience with at least one major ML framework, such as TensorFlow or PyTorch
- Exposure to MLOps and machine learning workflow orchestration; experience with AWS SageMaker is a plus
- Strong communication and interpersonal skills, with the ability to work effectively across technical and non-technical partners
- Interest in staying current with AI research and applying new techniques responsibly in production
- Healthcare technology experience is a plus, but not required
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