Experience:

• 3+ years of professional experience in ML/AI engineering or closely related role
• Experience deploying ML models to production including model serving, monitoring, versioning

Responsibilities:

• Develop structured application code with packaging, testing, and CI/CD
• Work directly with clinicians and operations staff who are not engineers

Additional responsibilities:

• Strong communication skills

Nice to have:

• Experience in healthcare/finance or other regulated industries
• Familiarity with HIPAA compliance, BAA requirements, PHI handling
• Familiarity with EHR data formats and standards (HL7, FHIR R4, X12 837/835)
• Experience with Temporal or similar workflow orchestration frameworks (Airflow, Prefect)
• Background in voice/speech tech including ASR model evaluation, Whisper fine-tuning, telephony integration (Twilio/SIP)
• Exposure to React/Next.js for building internal ML-powered tools and dashboards
• Experience with MLOps tooling including experiment tracking (MLflow, W&B), feature stores, model registries

More skills:

predictive modeling, TensorFlow, LLM integration, speech/NLP pipelines, REST APIs, Git, SQL, Docker, infrastructure-as-code, GCP services, Cloud Run, Cloud SQL, BigQuery, Vertex AI, AWS SageMaker, Azure ML

Other:

• Tech stack includes Python (primary), TypeScript/JavaScript
• Backend technologies: FastAPI, Temporal
• Frontend technologies: React, Next.js
• Database: PostgreSQL (Cloud SQL)
• Cloud infrastructure: GCP (Cloud Run, Vertex AI, BigQuery, Artifact Registry, Secret Manager)
• Infrastructure tools: Terraform, Docker, GitHub Actions
• ML/AI tools: PyTorch, scikit-learn, Hugging Face, LangChain, Claude API, OpenAI API
• Voice technologies: SIP, Whisper, Google MedASR
• Data tools: Pandas, dbt, BigQuery
• Pay range: ₹408,424.75 - ₹1,279,213.11 per year
• Benefits include commuter assistance, food provided, health insurance, paid sick time, paid time off, Provident Fund