Senior ML/AI Engineer

TailorCare

. Build the decisioning and feedback layer between model scores and actions, including action selection, holdout and experiment assignment, outcome capture, and lift measurement .

Posted 11/3/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production ML models, integrating real-time event-driven systems, and managing AWS-native infrastructure while ensuring compliance with PHI controls. Proficient in mentoring teams and establishing engineering standards for ML practices.

Highest-signal resume keywords

ML EngineeringAWS Data ServicesDatabricksEvent-Driven SystemsPython

ATS Keywords

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Hard Skills

Machine LearningModel DeploymentPredictive ModelingCI/CDSQLData ScienceModel MonitoringInfrastructure as CodeStreaming SystemsFeature Engineering

Soft Skills

MentoringCollaborationCommunication

Tools & Technologies

DatabricksPySparkDelta LakeMLflowTerraformKinesisKafkaScikit-learnXGBoostPyTorch

Industry Keywords

Healthcare DataPHI HandlingDecisioning SystemsExperimentation SystemsLLM Applications

Tech Stack

Tools & technologies

AWSKafkaPySparkPythonPyTorchScikit-LearnSQLTerraform

About the role

Key responsibilities & impact

Build the decisioning and feedback layer between model scores and actions, including action selection, holdout and experiment assignment, outcome capture, and lift measurement
Design and build event-driven, real-time integrations between model outputs and operational systems, including streaming pipelines, schemas, replay, ordering, and failure handling
Instrument and manage compute, streaming, inference, and LLM costs with budgets and alerts
Deploy, monitor, and retrain production ML models using CI/CD, model registries, and alerting for drift, coverage, and calibration
Build and improve predictive models using healthcare claims, authorization, and operational data
Expand AWS-native infrastructure alongside the Databricks lakehouse using infrastructure as code, IAM, secure data handling, containerized inference, and managed foundation-model services under PHI controls
Extend the feature store and data assets toward real-time features
Own production GenAI applications, including LLM pipelines and agentic workflows with evaluation, retrieval, guardrail, and cost controls
Partner with data scientists, data engineering, and software engineering on production models, pipelines, interfaces, and contracts
Establish engineering standards through code review, automated testing, reproducibility, documentation, and release discipline
Mentor data scientists on production practices
Report to the Director, AI & Decision Intelligence and collaborate with clinical and operations partners

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience
5+ years in ML engineering, MLOps, or data science, including 3+ years operating ML systems in production
Production experience with Databricks, PySpark, Delta Lake, and MLflow
Production experience with AWS data and ML services and infrastructure as code (Terraform, CDK, or CloudFormation)
Hands-on experience designing and running event-driven or streaming systems (Kinesis, Kafka, or equivalent) with schema or contract management
Strong Python and SQL
Experience building and evaluating ML models with scikit-learn, XGBoost, or PyTorch
CI/CD for ML workloads and model and pipeline monitoring
Ability and willingness to travel up to 10% as needed for onsite meetings, team collaboration, and company events
Desired: experience with recommendation, decisioning, or experimentation systems; dbt; healthcare data and PHI handling; containerized model serving; Amazon Bedrock or managed foundation-model platforms under a HIPAA BAA; agentic frameworks; retrieval systems; LLM applications, evaluation, and guardrails

Benefits

Comp & perks

Meaningful work and mission-driven environment
Remote-first work environment with options for a hybrid work model in Nashville
Generous paid time off (PTO) and holiday plans
Paid parental leave
Flexible work-life balance and autonomy
Medical, dental, vision, life, and disability insurance from Day 1
Wellness resources
Employer HSA contribution
401(k) plan with employer matching
Inclusive community and collaborative work environment