Machine Learning Ops Engineer
Careforth · United States
Hospitals and Health Care · 501-1,000 employees
About the role
The ML Ops Engineer will design and maintain scalable infrastructure for ML models, including automated pipelines, model serving, and monitoring. They will collaborate with data scientists to ensure models are deployable, HIPAA-compliant, and continuously improved.
What they look for
Requirements
Candidates must have at least 7 years of professional experience in DevOps, Data Engineering, or ML Engineering, with 4 years specifically in MLOps. A Bachelor's or Master's degree in Computer Science or a related field is required, along with expertise in AWS, containerization, and ML lifecycle tools.
Benefits
Full description
About Us
A pioneer in the caregiving space, Careforth supports family caregivers across the United States to confidently care for their loved ones at home. Through a combination of in-person home visits, remote coaching and our proprietary digital collaboration app, we provide caregivers with support, guidance, confidence, and connection to resources they need. The Caregivers and families we support stay with Careforth for many years, building lasting relationships along the way. Join us today and live our values: lead with heart, cultivate trust, go beyond.
Position Summary
The ML Ops Engineer is a critical specialist within the Product & Technology Organization, responsible for the intersection of machine learning, software engineering, and platform operations. You will design and maintain the infrastructure required to scale ML models across clinical risk intelligence, caregiver risk scoring, composite risk trajectory, NLP signal capture, LLM-powered enablement tools, and insights reporting — from research through reliable production.
The ideal candidate has deep experience with distributed systems, containerization, model lifecycle governance, and automated ML pipelines, and thrives collaborating with Data Scientists and Data Engineers to ensure models are deployable, monitorable, HIPAA-compliant, and continuously improving.
What You Will Do
- Design and implement automated ML pipelines for model training, evaluation, and deployment using MLflow, Databricks Workflows, and AWS SageMaker Pipelines; own model registry governance including versioning, promotion, and retirement.
- Build and manage scalable model serving infrastructure (REST APIs, WebSocket APIs) using Docker and Kubernetes/EKS for real-time and batch scoring across all risk and enablement model domains.
- Architect and operate a sub-model orchestration layer, score computation service, score history, and audit logging compliant with HIPAA requirements.
- Design and maintain feature store architecture, temporal feature computation, and data versioning to ensure training-serving consistency across all ML domains.
- Implement and govern LLM API integrations (Claude/GPT via Bedrock) including prompt versioning, rate limiting, cost tracking, response logging, and output guardrails.
- Build production monitoring and alerting for data drift, model decay, scoring latency, and pipeline failures; implement A/B testing infrastructure for controlled model rollouts.
- Automate ML infrastructure provisioning using Terraform or AWS CloudFormation; manage secrets, access controls, PHI redaction, and HIPAA-compliant data handling across all services.
- Help define and lead the enterprise MLOps platform strategy, drive adoption of core tooling, and mentor junior engineers on operational standards and best practices.
- Establish CI/CD and Continuous Training (CT) workflows to enable rapid, safe, and auditable ML iteration across all project domains.
- Perform other duties and special projects as assigned.
What You Will Bring
Education
- Bachelor's or Master's Degree in Computer Science, Software Engineering, or a related technical field.
Experience
- 7+ years of professional experience in DevOps, Data Engineering, or ML Engineering, with at least 4 years focused on Machine Learning operations.
- Proven track record of owning and operating production ML systems including model serving, monitoring, and lifecycle governance.
- Experience in healthcare or regulated data environments; familiarity with HIPAA technical safeguards required.
- Experience mentoring engineers and contributing to platform standards and technical roadmaps.
Technical Skills
- Expert-level containerization and orchestration: Docker, Kubernetes/EKS; Infrastructure-as-Code with Terraform or AWS CloudFormation.
- Deep experience with ML lifecycle tooling: MLflow, Databricks (Delta Lake, Unity Catalog, Workflows, Spark, Vector Search), and AWS SageMaker.
- Strong AWS proficiency: S3, Lambda, API Gateway, SageMaker, Bedrock, Redshift, Athena, DynamoDB, Glue, Step Functions, Kinesis, Transcribe, Comprehend Medical, Secrets Manager.
- Experience with stream processing (Kafka/Kinesis), event-driven pipeline design, and feature store architecture.
- Familiarity with LLM API integration, prompt versioning, RAG infrastructure, and LLM quality and cost governance.
- Strong Python proficiency; Bash scripting; Go or Java a plus.
Soft Skills
- Clear communicator able to translate operational constraints into actionable guidance for Data Scientists and product teams.
- Collaborative, detail-oriented, and committed to reproducibility, HIPAA audit-readiness, and operational excellence.
- Self-directed and intellectually curious; proactive in evaluating and adopting emerging MLOps tooling.
You'll Benefit From
At Careforth your well-being matters. With flexible schedules, a remote-first culture, and a nationally recognized wellness program, our benefits are designed to help you thrive, both professionally and personally. Discover how we invest in you: https://careforth.com/careers/#benefits
The pay range for this position is $111,000 - $175,000. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and geographic location.
Join Our Award Winning Team
Founded in Boston, Careforth's caregiver programs and services improve health outcomes, keeping care at home longer. Additionally, our programs provide financial benefit to caregivers and cost savings to state agencies and health plans. At Careforth, we understand the challenges of caregiving and are committed to supporting family caregivers at every turn.
Caregivers play a critical role in the future of healthcare—and so can you.
Apply now!
For more information, please visit www.Careforth.com.
Careforth is an Equal Opportunity Employer*
DISCLAIMER: Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job.
*Careforth supports families with diverse backgrounds and as an equal opportunity employer, we seek employees who reflect the diverse population we serve. Careforth complies with all applicable laws concerning hiring and employment practices and is firmly committed to fostering and maintaining a workplace free from discrimination. We pledge to hire, train, and promote our employees without regard to race, religion, gender, gender identity, genetic information, age, national origin, sexual orientation, disability, veteran status, or any other category protected by applicable law.
Careforth strives to create experiences that are accessible and welcoming to everyone, including making www.careforth.com and the careers site accessible to any and all users. If you would like to contact us regarding the company’s diversity, equity and inclusion initiatives, inquire about a specific accessibility need or the accessibility of our website, or if you need assistance completing an application process, please contact People & Culture at 866-797-2333.