AI/ML Engineer

Overview

Remote
On Site
Hybrid
BASED ON EXPERIENCE
Contract - W2
Contract - Independent

Skills

Backend Development
Software Engineering
Autogen
Reasoning
Cloud Computing
Amazon Web Services
Machine Learning Operations (ML Ops)
React.js
Python
Artificial Intelligence
Machine Learning (ML)
Natural Language Processing
Generative Artificial Intelligence (AI)
Evaluation
LangChain
LlamaIndex
PyTorch
TensorFlow
Optical Character Recognition
Orchestration
Management
Microsoft Certified Professional
LangSmith

Job Details

Job Title: AI/ML Engineer
Location: London/NY time zone hours / Canada
Job Type: Contract

Required Qualifications

  • 7+ years in software engineering or applied ML building real-world AI/ML systems; strong Python proficiency and backend development expertise.
  • Hands-on experience building GenAI apps with LangChain and LangGraph, including agent design, state/memory management, and graph-based orchestration.
  • Proficiency in ML/NLP and generative models; experience with embeddings, vector stores, RAG, and LLM integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.)
  • Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow; solid understanding of software engineering fundamentals and secure development.
  • Experience with AI agent frameworks and MCP; familiarity with agent observability (LangSmith/LangFuse) and agentic RAG patterns
    Track record of delivering scalable, production AI systems and collaborating across teams.
  • Experience with agent frameworks (AutoGen, CrewAI), tool-use ecosystems, and advanced planning/reasoning strategies
  • Knowledge of cloud platforms (AWS), MLOps, and data pipelines; React.js familiarity is a plus.
  • Exposure to enterprise environments and secure, compliant deployments

Key Skills

Programming: Python; backend APIs (FastAPI)
AI/ML: ML/NLP, generative AI, embeddings, model evaluation
Frameworks: LangChain, LangGraph; plus LlamaIndex, PyTorch, TensorFlow, MLflow
Architectures: RAG, Transformers, OCR
Agents: Design and orchestration, memory/state management, tool integration; MCP and agent-to-agent protocols
Observability: LangSmith/LangFuse for agent monitoring

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