Machine Learning Engineer III

JOB SUMMARY: We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative team. The ideal candidate will have a strong background in developing, deploying, and optimizing machine learning models, as well as expertise in data ingestion and modeling techniques. This role requires a deep understanding of hospital operations, healthcare data, clinical workflows, and regulatory requirements (such as HIPAA or GDPR). The successful candidate will be passionate about leveraging advanced technologies to enhance patient care and operational efficiency.

PRIMARY DUTIES AND RESPONSIBILITIES

• Design, develop, and implement machine learning and deep learning models to address hospital-specific challenges such as patient flow optimization, resource allocation, bed management, and predictive analytics for patient outcomes.
• Build and optimize data ingestion and modeling pipelines as needed
• Utilize domain driven techniques and design patterns to build and contribute to technical
• design.
• Collaborate with cross-functional teams including data scientists, software engineers, clinicians, hospital administrators, and experts to identify and develop high-impact machine learning solutions.
• Work with large-scale healthcare and hospital datasets including structured data (EHRs, hospital operational data), unstructured data (clinical notes, imaging).
• Ensure data privacy and security, adhering to healthcare regulations such as HIPAA and GDPR, especially when working with sensitive hospital data.
• Mentor junior engineers and data scientists, providing guidance on machine learning techniques, particularly those relevant to hospitals and healthcare systems.
• Monitor, troubleshoot, and enhance the performance of deployed models using MLOps best practices, ensuring they operate effectively in hospital environments.
• Write technical architectural and design documents.

EDUCATION

• Master’s or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 5 or more years of experience.
• Bachelor’s degree in computer science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 7 or more years of experience.

TECHNICAL EXPERIENCE

• Must have some experience with Time Series Models
• Proven experience in end-to-end design and deployment of machine learning models from ideation to production in healthcare or similar settings.
• Strong programming skills and experience with object or component-oriented development software, one or more of: Python or R, with proficiency in ML frameworks, one or more of: TensorFlow, PyTorch, or Scikit-learn.
• Expertise in NLP, computer vision, or other specialized machine learning techniques applicable to healthcare and hospital environments.
• Deep knowledge of a scripting or statistical programming language (Python preferred). Ability to efficiently work with very large datasets and deal with non-standard machine learning datasets (class-imbalances, sparse matrices, etc.)
• Assess model performance; train multiple models; carry out tuning. Run A/B tests on models.
• Comfortable writing complex SQL queries and developing python packages.
• Experience with cloud-based management and hosting, one or more of: AWS, Azure, GCS, CloudFormation, Terraform, or Ansible. Interest in developing services as well as the underlying infrastructure
• Experience with database management system software, one or more of: Oracle, MSSQL, MongoDB, MySQL, DynamoDB, or PostgreSQL.
• Experience with Version Control Software, one or more of: git, Mercurial, CVS, TFS, or Subversion.

SKILLS

• Must have some experience with Time Series Models
• Strong understanding and experience executing several software development methodologies and life cycles. Ability to understand and translate business requirements into technical specifications.
• Experience with agile development practices.
• Excellent written and oral communication skills. Adept and presenting complex topics, influencing, and executing with timely / actionable follow-through.
• Strong analytical and problem-solving skills with the ability to convert information into practical training deliverables. Uses rigorous logic and methods to solve difficult problems.
• Knowledge of clinical workflows and hospital operations, and how technology can enhance efficiency and patient care.
• Familiarity with healthcare-specific machine learning challenges, such as data imbalance, longitudinal data, and real-time processing in hospital environments.
• Be an active listener, probe requirements for all projects from relevant stakeholders, stay nimble and willing to produce rapid iterations.