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AI-ML Engineer & Senior AI-ML Engineer

YO IT Group • Full-time • New York, NY, US • $132,000 - $154,000 / year • 1m ago

Experience

Years: 5 - 15 Years

Must Have

3+ years in building and deploying machine learning systems in production
Deep expertise in Python and modern AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers)
Experience with large language models (OpenAI, Anthropic, Cohere, open source LLMs) and prompt engineering

What You’ll Do

Architect and implement advanced AI and machine learning systems that solve complex business problems
Lead the design and deployment of LLM-based applications using frameworks like LangChain, LlamaIndex, and vector databases
Develop end-to-end ML pipelines from data acquisition and model training to deployment and monitoring
Design and build AI copilots, agents, and generative workflows that integrate seamlessly into modern software ecosystems
Apply deep expertise in NLP, computer vision, or predictive modeling to build intelligent, real-time systems
Evaluate and fine-tune foundation models for custom enterprise use cases
Collaborate with cross-functional product, design, and engineering teams to define intelligent experiences
Explore and implement retrieval-augmented generation (RAG), semantic search, and multi-modal reasoning techniques
Contribute to internal AI frameworks, toolkits, and accelerators to speed up solution delivery
Mentor engineers on AI architecture, model lifecycle best practices, and ethical/secure use of machine learning

Requirements

You’ll bring:

5+ years of software engineering experience with a strong focus on AI/ML and intelligent systems
3+ years in a technical leadership role, building and deploying machine learning systems in production
Deep expertise in Python and modern AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers)
Experience with large language models (OpenAI, Anthropic, Cohere, open source LLMs) and prompt engineering
Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and scalable ML infrastructure
Knowledge of AI system design, data engineering for ML, model evaluation, and MLOps practices
Strong understanding of NLP, generative AI, embeddings, and semantic search
Experience integrating AI capabilities into full-stack applications and cloud-native environments, specifically within AWS
Strong communication skills and a consulting mindset—able to confidently lead client-facing discussions on AI strategy
Passion for experimentation, innovation, and shaping the future of applied AI

Skills: machine learning,embeddings,ml,cloud-native environments,semantic search,mlops,nlp,generative ai,pytorch,data engineering for ml,ai/ml libraries,artificial intelligence,prompt engineering,tensorflow,python,hugging face transformers,large language models,aws,predictive modeling,mlops practices,cloud technologies,computer vision,open source,open ai,vector databases