Lead ML/AI Engineer

🔥 13 hours ago

🎸 Tennessee – Remote

🎸 Tennessee – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 13%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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TailorCare

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

⚕️ Healthcare Insurance

Healthcare • Healthcare Insurance

TailorCare is a healthcare company that specializes in providing personalized care solutions for patients with musculoskeletal (MSK) issues, such as joint, back, and muscle pain. It empowers patients by connecting them with specialists, coordinating appointments, and assisting in treatment decisions. TailorCare uses a patient-centered approach, featuring Clinical Navigators who are licensed physical therapists, to support patients throughout their care journey. They collaborate closely with primary care providers, specialty care providers, and payers to deliver evidence-based treatment options that optimize health outcomes and enhance the patient experience.

📋 Description

• Own the decisioning and feedback layer between model score and action, including action selection and ranking, holdout and experiment assignment, outcome capture, production ROI calculation, and lift-per-action and channel measurement pipelines • Own the engineering implementation, auditability, and reproducibility of the production savings calculation • Design event-driven, real-time integrations between model output and action systems, including streaming pipelines, versioned schemas and contracts, replay, ordering, idempotency, and failure handling • Own contracts with partner teams • Define per-model and per-decision budgets for compute, streaming, inference, and LLM spend • Make cost a release criterion alongside latency and accuracy • Define the production bar for ML models, including CI/CD, model registry, alerting, drift, coverage, and cohort, market, and payer calibration • Engineer model and ranking promotion gates before production release • Own target architecture and technical roadmap across AWS-native services and the Databricks lakehouse • Lead infrastructure as code, IAM, secure data handling, containerized inference, and managed foundation-model services under PHI controls • Set technical direction and production standards for GenAI applications, LLM pipelines, and agentic workflows • Establish evaluation, retrieval, guardrail, and cost controls for patient-data applications • Partner with data science, medical economics, data engineering, software engineering, clinical, and operations teams • Set team engineering standards for code review, automated testing, reproducibility, documentation, and release discipline • Lead design reviews, document architecture decisions, and mentor engineers and data scientists • Represent the team's technical position with R&D leadership, finance, clinical, and operations partners • Perform other duties as assigned

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience • 8+ years in ML engineering, MLOps, or software engineering • 4+ years operating ML systems in production • 2+ years as the technical lead or architect of a production ML or decisioning system • Experience building or operating prescriptive production systems such as recommendation, decisioning, prioritization, or experimentation platforms • Production experience with AWS data and ML services and infrastructure as code, including Terraform, CDK, or CloudFormation • Production experience with Databricks, PySpark, Delta Lake, MLflow, or equivalent • Hands-on experience designing and running event-driven or streaming systems such as Kinesis or Kafka with schema or contract management • Strong Python and SQL • Hands-on experience running ML workloads in production, including training pipelines, model serving, feature systems, or ML platform tooling • CI/CD for ML workloads and model and pipeline monitoring, including calibration across heterogeneous populations • Track record of setting engineering standards and raising the bar on a team through review and mentorship • Ability and willingness to travel up to 10% for onsite meetings, team collaboration, and company events • Preferred: scikit-learn, XGBoost, or PyTorch • Preferred: healthcare economics or value-based care exposure • Preferred: dbt and lakehouse data modeling • Preferred: healthcare data and PHI handling requirements • Preferred: uplift modeling, bandit or sequential decisioning, or holdout-based measurement • Preferred: containerized model serving and staged or canary deployment patterns • Preferred: Amazon Bedrock or other managed foundation-model platforms under a HIPAA BAA • Preferred: agentic frameworks and retrieval systems • Preferred: LLM-based applications, including evaluation and guardrails

🏖️ Benefits

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

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