Nicoll Curtin

Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a contract basis in Middletown, NJ. Key skills required include LLMs, prompt engineering, agentic AI frameworks, vector databases, and Python (FastAPI/Flask). Telecom experience is a plus.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 11, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Middletown, NJ
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🧠 - Skills detailed
#Kubernetes #AI (Artificial Intelligence) #Python #AWS (Amazon Web Services) #Langchain #Flask #TensorFlow #Deep Learning #Docker #PyTorch #FastAPI #Azure #Databases #GCP (Google Cloud Platform) #ML (Machine Learning)
Role description
We’re partnering with IBM on an exciting hands‑on ML Engineer role supporting AT&T’s next‑gen AI initiatives in Middletown, NJ. If you love building real LLM applications (not just research), this is for you. 📍 Location: Middletown, NJ (Hybrid – onsite required) 💼 Type: Contract ✨ What You’ll Work On • Build production‑grade LLM applications (OpenAI / Azure OpenAI) • Prompt engineering, function calling & RAG pipelines • Develop agent workflows (LangChain, LangGraph, CrewAI, AutoGen) • Work with vector databases (pgvector, Pinecone, Chroma, Weaviate) • Build Python services using FastAPI / Flask • Fine‑tune + evaluate models (PyTorch / TensorFlow) • Integrate APIs + orchestrate workflows at scale • Collaborate with IBM + AT&T engineering teams on advanced GenAI systems ✔️ Must‑Have Skills • LLMs (OpenAI / Azure OpenAI or similar) • Prompt engineering + RAG • Agentic AI frameworks (LangChain / LangGraph / CrewAI / AutoGen) • Vector databases (pgvector / Pinecone / Chroma / etc.) • Python backend (FastAPI / Flask) • Deep Learning (PyTorch / TensorFlow) ➕ Nice to Have • Azure, AWS, or GCP • Docker / Kubernetes • Real‑time systems, Document AI, Voice AI • Telecom background (AT&T, Verizon, T‑Mobile, etc.) 🔥 Who This Is For You’re a hands‑on builder who has shipped GenAI/LLM applications to production — not someone who’s only worked in research or experiments. You know how to take a model, optimize it, integrate it, and deploy it at scale.