WHAT WE ARE LOOKING FOR:

• Seven or more years of hands-on AI/ML engineering experience, with at least three years in a technical leadership or management position 

• Solid grasp of foundational AI/ML model architectures, including transformer models and how they compare to and interact with diffusion-based approaches 

• Production delivery experience across at least one of: agentic systems, LLM applications, computer vision, or time-series forecasting 

• Working knowledge of LLM application development: prompt engineering, RAG, fine-tuning, and evaluation 

• Familiarity with agentic frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or CrewAI. Candidates who built custom orchestration before these tools existed are equally welcome 

• Python proficiency with strong ML engineering fundamentals. PyTorch is required; ONNX and BentoML experience is a meaningful advantage for model serving and deployment 

• Practical MLOps experience: CI/CD for ML, model monitoring, feature stores, and experiment tracking 

• Cloud platform experience across Azure (Azure AI Foundry, Azure ML), AWS (Bedrock, SageMaker), or GCP (Vertex AI) 

• Ability to communicate technical decisions clearly to both engineering teams and senior client stakeholders 

• A track record of building and developing engineering teams 

BONUS POINTS:

• Experience designing human-in-the-loop workflows and escalation logic for autonomous AI systems 

• Familiarity with responsible AI frameworks, bias detection, and model governance in agentic contexts 

• Open-source contributions, custom framework development, or published work on agentic systems 

• Experience in regulated industries where autonomous AI carries additional compliance and oversight requirements 

KEY SKILLS:

Python | PyTorch | ONNX | Agentic AI | LLMs | Computer Vision | MLOps | Azure ML | Responsible AI

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