Job Description : We're looking for a versatile Full Stack AI/ML Engineer who can architect, build, and deploy production-grade AI/ML systems on AWS infrastructure.This role combines deep expertise in foundation models, healthcare data standards, and serverless cloud architecture to create scalable, secure, and compliant AI solutions for healthcare organizations.Essential Duties & Responsibilities : AI/ML Engineering : - Design and implement production foundation model applications using prompt engineering techniques including structured output design, few-shot learning, function-calling patterns, and hallucination mitigation strategies.- Build and optimize vector search solutions using OpenSearch Serverless with k-NN, including HNSW/IVF parameter tuning, hybrid retrieval (lexical + semantic), and multi-stage ranking pipelines (BM25 + dense + re-ranking).- Develop and deploy Amazon Bedrock solutions leveraging Claude family models, Titan Embeddings v2, and Guardrails for PHI/PII detection while optimizing for provisioned vs on-demand throughput.- Implement classical ML pipelines including clustering algorithms (HDBSCAN, k-means), confidence score calibration (Platt scaling, isotonic regression), and model evaluation frameworks.Healthcare Data & Standards : - Design and implement systems that work with FHIR R4 resources, HL7 v2 message structures, and USCDI data elements.- Build ontology retrieval systems against LOINC, SNOMED, and RxNorm terminologies to support clinical decision-making and data normalization.- Ensure HIPAA compliance and implement appropriate security controls for protected health information (PHI).Backend & Infrastructure : - Build high-performance APIs using FastAPI and Pydantic v2 with async I/O patterns, robust retry/backoff mechanisms,



and structured error handling.- Design and deploy AWS serverless architectures including Lambda (Python + container), API Gateway (REST + Step Functions, EventBridge, SQS, and SNS.- Implement container-based workloads on ECS Fargate with auto-scaling policies, service discovery, and Fargate Spot optimization.- Architect data solutions using Aurora PostgreSQL Serverless v2, DynamoDB, and S3 with appropriate indexing, partitioning, caching, and lifecycle policies.- Write production-grade Infrastructure as Code using AWS CDK (TypeScript or Python) supporting multi-tenant provisioning and cross-account deployments.Observability & Security : - Implement comprehensive observability using AWS X-Ray distributed tracing, CloudWatch metrics/logs/alarms, structured JSON logging, and correlation ID propagation.- Apply security engineering best practices including IAM least-privilege roles, KMS envelope encryption, Secrets Manager rotation, JWT validation, tenant isolation via session tags, and OWASP API Top-10 awareness.Evaluation & Quality : - Design rigorous evaluation frameworks including benchmark creation, per-class F1/precision/recall metrics, held-out test sets, label leakage prevention, and statistical significance testing for model comparisons.- Implement prompt versioning and A/B testing frameworks to continuously improve model performance.Qualifications : Technical Skills : - Python Stack : Proficiency with pydantic v2, pandas/polars, fastapi, boto3, asyncio,



and prompt-template libraries.- Foundation Models : Hands-on experience with prompt engineering, structured output generation, and evaluation harnesses for LLMs.- AWS Services : Production experience with Lambda, API Gateway, Step Functions, EventBridge, SQS, SNS, ECS Fargate, Aurora PostgreSQL, DynamoDB, S3, and AWS CDK.- Vector Search : Practical knowledge of OpenSearch Serverless, k-NN algorithms, hybrid retrieval, and ranking optimization.- Machine Learning : Experience with scikit-learn, clustering algorithms, and confidence calibration techniques.- Healthcare Standards (preferable) : Working knowledge of FHIR R4, HL7 v2, USCDI, LOINC, SNOMED, and RxNorm.- Security : Robust understanding of IAM, KMS, secrets management, and OWASP security principles.Experience : - 8 - 15 years of software engineering experience with at least 3 years focused on AI/ML systems.- Proven track record of deploying production ML systems at scale.- Experience with healthcare data or regulated industries strongly preferred.- Demonstrated ability to design and implement end-to-end ML evaluation frameworks.Soft Skills : - Strong problem-solving abilities and attention to detail.- Excellent communication skills for collaborating with cross-functional teams.- Self-motivated with ability to work independently and drive projects to completion.- Commitment to code quality, testing, and engineering best practices.Preferred Qualifications : - Experience with Amazon Bedrock and Claude family models.- Familiarity with HIPAA compliance requirements and healthcare security standards.- Contributions to open-source ML or healthcare interoperability projects.- Degree in Computer Science, Machine Learning, or related field. (ref:hirist.tech)

📌 ELLKAY - Senior Machine Learning Engineer (India)
🏢 ELLKAY
📍 India