ML Engineer

Title: ML Engineer
Location: Manhattan, NY
Work Model: Hybrid, 3 days per week at NY office location
Employment Type: Contract or Fulltime

Role Overview
The ML Engineer LLM Platforms & Assistants will design, build, and operate production-grade large language model (LLM) pipelines primarily within AWS-based environments. This role focuses on integrating OpenAI models into modular Python services, implementing Retrieval-Augmented Generation (RAG) and semantic search, and deploying scalable, secure, and observable AI assistants.
Key Responsibilities
Design and maintain LLM integrations using OpenAI APIs within AWS environments.
Build Python-based LLM services deployed on AWS compute platforms (ECS, EKS, Lambda, or EC2).
Implement RAG workflows and semantic search using AWS data and storage services.
Develop LangChain or agentic workflows supporting reasoning and tool use.
Integrate LLM pipelines with ETL/ELT workflows and enterprise data systems.
Deploy and integrate MCP servers and emerging orchestration tools.
Apply AWS security best practices using IAM, KMS, and Secrets Manager.
Implement monitoring and observability using CloudWatch and related tools.
Migrate custom GPT solutions into production-grade AWS-hosted assistants.
Ideal Candidate Profile
4 7+ years in software, ML, or applied AI engineering.
Strong Python proficiency.
Experience with RAG and semantic search.
Hands-on OpenAI LLM integration experience.
Experience deploying systems in AWS (S3, Lambda, ECS/EKS, IAM).
Preferred Qualifications
Experience with Amazon Bedrock.
AWS data services: Glue, Athena, OpenSearch, Aurora.
ETL/ELT pipeline development.
LLM orchestration and reasoning workflows.
Benchmarking and LLM evaluation.
Infrastructure as Code (CDK, CloudFormation, Terraform).
Education
Bachelor s degree in Computer Science, Engineering, Information Systems, or equivalent experience.