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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and optimizing machine learning systems, particularly in extracting and structuring knowledge from unstructured sources. Proficient in MLOps practices and familiar with cloud platforms, ensuring compliance with HIPAA standards in healthcare applications.
Highest-signal resume keywords
Machine Learning Systems DevelopmentLLM-Based Agentic SystemsRetrieval-Augmented Generation (RAG)Python ProgrammingMLOps Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningSoftware EngineeringData StructuresAlgorithmsAPI DesignKnowledge GraphsPredictive MLEvaluation MetricsOrchestrationTool Calling
Soft Skills
Clear CommunicationCollaboration Across TeamsComfort with Ambiguity
Tools & Technologies
AzureAWSLangGraphGoogle ADK
Industry Keywords
HIPAA ComplianceHealthcareRegulated IndustryPHI Handling
Tech Stack
Tools & technologiesAWSAzureCloudPython
About the role
Key responsibilities & impact- Build systems that ingest unstructured and inconsistent source material, such as policies, protocols, rules, and spreadsheets, and turn it into structured, versioned, and verified knowledge
- Build extraction, normalization, and validation pipelines using LLMs and classical techniques; detect conflicts, gaps, and stale information, and route uncertain cases to human review
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines that give downstream systems and agents accurate, grounded, and traceable answers with low latency
- Build, ship, and maintain components of agentic systems, including orchestration, tool calling, and state management
- Build evaluations including ground-truth datasets, accuracy metrics, regression tests, LLM-as-judge, human review, and production quality monitoring
- Diagnose and improve accuracy, latency, reliability, and cost of ML systems in production
- Build reusable components across DexCare’s AI products and contribute to other products as priorities shift
- Follow ML lifecycle best practices including versioning, deployment, monitoring, and retraining
- Handle patient and customer data in line with HIPAA and DexCare’s privacy and security standards
- Work closely with product, engineering, and data teams across DexCare’s AI products, including Optimize AI and Mila
Requirements
What you’ll need- 3-5 years of experience in machine learning or software engineering, including building and running production ML systems
- Experience building systems that extract, structure, and verify knowledge from unstructured sources, such as documents, policies, or operational data, with measurable accuracy
- Hands-on experience shipping LLM-based agentic systems to production, including orchestration, tool calling, and handling failures with retries and fallbacks
- Experience building retrieval systems and improving their accuracy and latency
- Experience evaluating ML and LLM systems: building eval datasets, defining metrics, and using the results to decide what ships
- Strong Python and software engineering fundamentals, including data structures, algorithms, testing, code review, and API design
- Familiarity with MLOps practices and at least one major cloud platform
- Clear communication and the ability to work across product, engineering, and data teams, including across time zones
- Comfort working in ambiguous problem spaces where requirements and data evolve
- Experience with agent frameworks such as LangGraph or Google ADK
- Experience with Azure / AWS and their ML and AI services
- Experience with knowledge graphs, rules engines, or other structured knowledge representations
- Experience with predictive ML or optimization for problems such as forecasting, scheduling, ranking, or matching
- Experience with guardrails, safety classifiers, or red-teaming for LLM applications
- Experience in healthcare or another regulated industry, including handling PHI under HIPAA