ML engineer

Overview

On Site
Full Time
Part Time
Accepts corp to corp applications
Contract - Independent
Contract - W2

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

Hiring: W2 Candidates Only

Visa: Open to any visa type with valid work authorization in the USA

Level: Mid to Lead positions

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

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.