ML Engineer
- NA
12 Hours Ago
NA
C2C
Dallas-TX
11-20 Years
Required Skills: GenAI, LLM, GPT, Claude, Gemini, Llama, Mistral, RAG, GraphRAG, Prompt Engineering, AI Agents, LangChain, LangGraph, LlamaIndex, Hugging Face, Pinecone, FAISS, ChromaDB, Milvus, Weaviate, PyTorch, TensorFlow, Python, NLP, Deep Learning, FastAPI, Docker, Kubernetes, MLflow, MLOps, Databricks, Apache Spark, AWS Bedrock, Azure OpenAI, Vertex A
Job Description
We are looking for a highly experienced Senior AI/ML Engineer with 10–12+ years of overall software engineering experience and extensive expertise in Machine Learning, Deep Learning, and Generative AI. The ideal candidate will have a proven track record of architecting, developing, and deploying enterprise-scale AI platforms powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
This role requires hands-on experience building scalable AI solutions, leading technical initiatives, mentoring engineering teams, and collaborating with cross-functional stakeholders to deliver innovative AI products.
Key Responsibilities
- Design, develop, and deploy enterprise-scale AI/ML and Generative AI solutions.
- Architect and implement LLM-powered applications using OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Llama, Mistral, or similar models.
- Design and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge management and intelligent search.
- Build AI-powered assistants, copilots, chatbots, document intelligence, and workflow automation solutions.
- Develop robust prompt engineering strategies and evaluation frameworks for LLM performance.
- Fine-tune open-source LLMs and optimize inference for production environments.
- Build scalable AI microservices and REST APIs using Python and FastAPI.
- Develop and maintain MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
- Work with vector databases such as Pinecone, FAISS, ChromaDB, Milvus, or Weaviate.
- Collaborate with Data Engineering teams to process large-scale structured and unstructured datasets.
- Lead architecture discussions, perform code reviews, and mentor junior AI engineers.
- Implement Responsible AI, model governance, security, explainability, and compliance best practices.
- Optimize AI applications for scalability, latency, reliability, and cost efficiency.
- Partner with business stakeholders to translate business requirements into AI-driven solutions.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.
- 10–12+ years of software engineering or AI/ML development experience.
- 5+ years of hands-on Machine Learning and Deep Learning experience.
- 3+ years of production experience with Generative AI and Large Language Models.
- Expert-level programming skills in Python.
- Strong understanding of NLP, Transformer architectures, embeddings, attention mechanisms, and vector search.
- Hands-on experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar orchestration frameworks.
- Experience integrating OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or open-source LLMs.
- Experience building RAG-based AI applications.
- Experience with Hugging Face Transformers and model fine-tuning.
- Strong knowledge of PyTorch and/or TensorFlow.
- Experience developing REST APIs using FastAPI or Flask.
- Experience with Docker, Kubernetes, Git, and CI/CD pipelines.
- Strong expertise in SQL and NoSQL databases.
- Excellent communication, leadership, and problem-solving skills.
Preferred Skills
- Agentic AI frameworks (CrewAI, AutoGen, LangGraph, Semantic Kernel)
- AI Agents and Multi-Agent Systems
- Databricks, Apache Spark, Delta Lake
- MLflow, Kubeflow, SageMaker
- Computer Vision and Multimodal AI
- Knowledge Graphs and Neo4j
- GraphRAG implementation
- Reinforcement Learning
- AI Security and Responsible AI
- Model evaluation frameworks and LLM observability
Cloud Technologies
Experience with one or more of the following cloud platforms:
- AWS (Amazon Bedrock, SageMaker, ECS, EKS, Lambda)
- Microsoft Azure (Azure OpenAI, Azure Machine Learning)
- Google Cloud Platform (Vertex AI)
Mandatory Technical Skills
- Python
- Machine Learning
- Deep Learning
- Generative AI (GenAI)
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- AI Agents
- LangChain
- LangGraph
- LlamaIndex
- Hugging Face
- OpenAI / Azure OpenAI
- Anthropic Claude
- Gemini
- Llama
- Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, Milvus)
- PyTorch
- TensorFlow
- FastAPI
- REST APIs
- Docker
- Kubernetes
- Git
- CI/CD
- MLOps
- MLflow
- AWS / Azure / GCP
- Databricks
- Apache Spark
Preferred Certifications
- AWS Certified Machine Learning – Specialty
- Microsoft Azure AI Engineer Associate
- Google Professional Machine Learning Engineer
- Databricks Certified Machine Learning Professional
