Staff Engineer, Machine Learning Operations

The Staff Engineer, Machine Learning Operations will architect, own, and scale the machine learning infrastructure and deployment pipelines that power Monogram's operational and clinical initiatives. Operating with full autonomy, you'll establish MLOps excellence, mentor engineering teams, and drive strategic technical decisions that directly impact patient outcomes. This role requires a seasoned engineer who can balance innovation with production reliability while building systems that handle healthcare's most sensitive and complex data. 

• ML Platform Ownership: Architect and maintain enterprise-grade ML infrastructure, including model versioning, automated testing frameworks, containerization strategies, CI/CD pipelines, and comprehensive monitoring systems for model performance, data quality, and drift detection. 

• Technical Leadership: Drive MLOps strategy and standards across the organization. Mentor data scientists and engineers on production best practices, system design, and scalable architecture patterns. 

• End-to-End Model Lifecycle: Own the complete journey from model development through production deployment, including real-time and batch inference systems, A/B testing frameworks, and automated retraining pipelines. 

• Cross-Functional Partnership: Collaborate with clinical leaders, product teams, and data scientists to translate complex healthcare requirements into robust, scalable ML solutions. Present technical strategies to executive stakeholders. 

• Production Excellence: Build fault-tolerant, compliant systems that meet healthcare security and privacy standards. Establish SLAs, incident response protocols, and disaster recovery procedures for mission-critical ML services. 

• Innovation & Scale: Evaluate and integrate cutting-edge MLOps tools and practices. Design systems that scale with Monogram's growth while reducing operational overhead and improving model iteration velocity. 

• Experience: 

• • 10+ years in software engineering with 5+ years focused on ML infrastructure, MLOps, or production ML systems 

• • 5+ years of Python development with strong software engineering fundamentals 

• • 3+ years architecting and deploying production ML systems on cloud platforms (Azure preferred) 

• • Proven track record building and scaling ML platforms from the ground up 

• • Healthcare or regulated industry experience strongly preferred 

• Technical Skills: 

• • Expert-level proficiency with MLOps tooling (MLflow, Kubeflow, SageMaker, Azure ML, etc.) 

• • Deep experience with containerization (Docker, Kubernetes), orchestration tools (Airflow, Prefect), and infrastructure-as-code (Terraform, ARM templates) 

• • Advanced knowledge of CI/CD systems, automated testing strategies, and GitOps workflows 

• • Strong data engineering skills: SQL, Spark/PySpark, Databricks, data pipeline optimization 

• • Expertise in model monitoring, observability, feature stores, and experiment tracking at scale 

• • Production experience with both batch and real-time inference architectures 

• • Understanding of healthcare data standards (FHIR, HL7, claims data) is a plus 

• Leadership & Communication: 

• • Demonstrated ability to influence technical direction and mentor senior engineers 

• • Exceptional communication skills with ability to distill complex technical concepts for diverse audiences 

• • Track record of driving consensus on architectural decisions across multiple stakeholders 

• Educational Background: 

• • Bachelor's degree in Computer Science, Engineering, or related field required 

• • Master's degree or equivalent practical experience preferred 

• Additional Skills: 

• • Systems thinking with focus on reliability, scalability, and maintainability 

• • Deep understanding of security, compliance, and privacy requirements in healthcare (HIPAA) 

• • Bias toward action with pragmatic approach to technical debt and iterative improvement 

• Comprehensive Benefits - Medical, dental, and vision insurance, employee assistance program, employer-paid and voluntary life insurance, disability insurance, plus health and flexible spending accounts 

• Financial & Retirement Support – Competitive compensation, 401k with employer match, and financial wellness resources 

• Time Off & Leave – Paid holidays, flexible vacation time/PSSL, and paid parental leave 

• Wellness & Growth – Work life assistance resources, physical wellness perks, mental health support, employee referral program, and BenefitHub for employee discounts  

Monogram Health is a leading multispecialty provider of in-home, evidence-based care for the most complex of patients who have multiple chronic conditions. Monogram health takes a comprehensive and personalized approach to a person’s health, treating not only a disease, but all of the chronic conditions that are present - such as diabetes, hypertension, chronic kidney disease, heart failure, depression, COPD, and other metabolic disorders.   

Monogram Health employs a robust clinical team, leveraging specialists across multiple disciplines including nephrology, cardiology, endocrinology, pulmonology, behavioral health, and palliative care to diagnose and treat health issues; review and prescribe medication; provide guidance, education, and counselling on a patient’s healthcare options; as well as assist with daily needs such as access to food, eating healthy, transportation, financial assistance, and more. Monogram Health is available 24 hours a day, 7 days a week, and on holidays, to support and treat patients in their home.  

Monogram Health’s personalized and innovative treatment model is proven to dramatically improve patient outcomes and quality of life while reducing medical costs across the health care continuum.