Sr. AIOps Engineer
About us
Health Data Analytics Institute (HDAI) is a care optimization, decision support and provider enablement company powered by big data, AI-driven analytics, expert insights, and point of care technology solutions to facilitate improved patient outcomes and greater efficiency. HDAI collaborates with leading health systems, value-based care organizations, physician groups, and payers to improve care delivery, population health and reduce cost and make efficient use of scarce clinical resources.
Job description
We are looking for an AIOps/MLOps Engineer to join our team at HDAI. This team owns our inference pipeline (deployment, CI/CD, monitoring), common tooling to bridge the gap between R&D and production, and an API layer to return inference results. In this role, you will be creating new pipeline components to deliver near real-time inference results, both with in-house models and LLMs, at a national scale. This role comes at a key turning point in our product development: We are transitioning from a legacy application to a Python-based, AWS-native, event driven architecture (you should be familiar with Lambdas, ECS, SQS, and S3, or similar technologies). Maintaining rigorous standards of quality assurance and code development are a core competency of this position – we pride ourselves on delivering model results to clinicians that they can trust. At HDAI, we nurture a culture of continually improving, and one of the best assets of our engineers is a love for learning. We hope that you too share this goal. A successful candidate will demonstrate strong attention to detail, clear communication, and effective follow-through. We are excited to have you as a part of this team!
Job responsibilities
- Contribute to the development of our new inference pipeline, model deployment pipeline, and model registry
- Participate in the development of a new the API layer between post-process + post-inference data and the frontend application
- Participate with test-driven development by writing unit and integration tests for your code
- Maintain software using agile best practices, document and fix bugs, update release notes, update documentation, and address backlog items on a regular basis
- Contribute to a collaborative work environment with peers across many teams
Qualifications
- 5+ years of working experience in either a data science role, as a machine learning engineer, or as an MLOps engineer with a background in mathematics or equivalent field of study
- Familiarity with developing for cloud platforms (AWS, Azure, GCP) and Docker
- Experience with AWS Lambdas, ECS, SQS, S3, as well as Terraform are a plus
- Proficient in implementing event-driven architectures composed of stateless services
- Extensive software development experience in Python or similar languages
- Applicants must possess a strong ability to diagnose and resolve complex software issues through effective debugging techniques
- Familiarity with RESTful APIs
- Comfortable working with Git and working on a team using agile/scrum
- Excellent interpersonal skills with demonstrated ability to effectively communicate with internal and external teams; ability to develop trust, cooperation, and mutual respect
Preferred education
Bachelor’s Degree in Computer Science or equivalent
EO statement
HDAI is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Job Type: Full-time
Pay: $150,546.00 - $175,367.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Flexible spending account
- Health insurance
- Paid time off
- Tuition reimbursement
- Vision insurance
Compensation Package:
- Bonus opportunities
- Stock options
Schedule:
- 8 hour shift
Experience:
- Machine learning: 5 years (Required)
- AWS Lambda: 5 years (Required)
- python: 5 years (Required)
- ETL data pipelines: 5 years (Required)
- Cloud computing (AWS,GCP,Azure): 5 years (Required)
Ability to Commute:
- Dedham, MA 02026 (Required)
Work Location: In person
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