Machine Learning Engineer

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🕒 3 days ago

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Logo of TeleHealth

TeleHealth

2 - 10 employees

Founded 2016

🏥 Healthcare

Healthcare

TeleHealth is a healthcare company (LinkedIn lists it under Hospitals and Health Care). TeleHealth offers telemedicine and virtual care services and/or platforms that enable remote patient–clinician interactions, remote consultations, and other digital health services.

📋 Description

• Development and tuning of agentic workflows: routing logic, tool use, context management, and prompt/config iteration • Evaluation frameworks that measure agent quality against real outcomes, not just spot checks • Production monitoring for agent behavior, including failure modes and escalation paths • Build the evaluation and validation framework for all agent-driven clinical recommendations — including safety guardrails, confidence thresholds, and human-in-the-loop escalation triggers for the Clinical Protocol Agent • Develop patient risk stratification models for adherence prediction, adverse event likelihood, dosage titration optimization, and churn/dropout risk using clinical, behavioral, and engagement signals • Implement and manage the predictive analytics pipeline on AWS — Amazon Forecast (DeepAR+) for time-series clinical predictions, S3 Vectors for embedding-based patient similarity and retrieval, and Bedrock for agent inference • Design and build the RAG architecture that grounds agent responses in clinical protocols, formulary data • Own model lifecycle management — training pipelines, feature stores, model versioning, A/B testing, drift detection, and retraining triggers in production • Build explainability layers for clinical recommendations • Collaborate with the clinical team to translate clinical protocols and pharmacy domain knowledge into model features, training labels, and validation criteria • Establish model monitoring and alerting — prediction quality dashboards, distribution shift detection, and automated alerts when model performance degrades below clinical safety thresholds • Work with the DevOps/AgentOps teammate to ensure all ML decisions are logged, reproducible, and auditable for regulatory review

🎯 Requirements

• Strong coding skills, with production experience in Python • Experience building and tuning agentic systems: multi-agent orchestration, tool use, retrieval-augmented generation, or LLM-based workflows • Experience shipping ML or AI features to production, not just prototypes • Comfort working with evaluation frameworks: building test sets, running evals, and iterating on prompts, tools, or configuration based on results

🏖️ Benefits

• Health care insurance (medical, dental, vision) • Life Insurance • Supplemental Insurance • PTO • 401K matching • Sick leave • Phone/internet reimbursement • Remote work • Top of the line machines

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