Senior Data Scientist / AI-ML Engineer- W2 ONLY

Role: Senior Data Scientist / AI-ML Engineer- W2 ONLY

Location: Dallas, TX ( Remote)

Job Description

We are seeking an experienced Senior Data Scientist / AI-ML Engineer to design, develop, deploy, and optimize scalable AI and machine learning solutions that solve complex business problems. The ideal candidate will have strong expertise in Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and MLOps, with hands-on experience delivering production-grade AI applications on cloud platforms.

Key Responsibilities

• Design, build, train, fine-tune, evaluate, and deploy Machine Learning, Deep Learning, and Generative AI models into production environments.

• Develop and implement LLM-powered applications using OpenAI, Claude, Llama, Gemini, and other foundation models.

• Build RAG pipelines using LangChain, LangGraph, LlamaIndex, vector databases, and embedding models for enterprise knowledge retrieval.

• Design and implement Agentic AI and multi-agent systems with autonomous planning, tool orchestration, memory, and workflow automation.

• Develop scalable feature engineering pipelines, ML pipelines, feature stores, model serving, and inference APIs.

• Build and maintain MLOps/LLMOps pipelines for model training, versioning, deployment, monitoring, drift detection, and automated retraining.

• Collaborate with cross-functional teams to integrate AI capabilities into customer-facing applications, APIs, and enterprise platforms.

• Translate complex business requirements into scalable AI/ML solutions with measurable business outcomes.

• Optimize AI models for performance, latency, scalability, security, and cost efficiency.

• Implement responsible AI practices including model evaluation, guardrails, governance, explainability, and monitoring.

Required Skills

• Strong programming experience in Python and SQL.

• Hands-on experience with Machine Learning, Deep Learning, NLP, Computer Vision, and predictive analytics.

• Strong experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, and Hugging Face Transformers.

• Expertise in Generative AI, LLMs, Prompt Engineering, RAG, AI Agents, MCP, Function Calling, and Multi-Agent Architectures.

• Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar AI orchestration frameworks.

• Hands-on experience with Vector Databases such as Pinecone, FAISS, ChromaDB, Weaviate, or PGVector.

• Experience deploying AI workloads on AWS (SageMaker, Bedrock, Lambda, ECS, EKS, S3), Azure AI, or Google Vertex AI.

• Experience with MLflow, Kubeflow, SageMaker Pipelines, Model Registry, CI/CD, and model monitoring.

• Knowledge of Docker, Kubernetes, REST APIs, Git, Terraform, and cloud-native architectures.

Preferred Qualifications

• Experience in Healthcare, Financial Services, Retail, Manufacturing, or Insurance domains.

• Experience building enterprise-scale GenAI, RAG, Conversational AI, AI Copilots, and Intelligent Automation solutions.

• Knowledge of AI governance, security, compliance, and Responsible AI best practices.

• AWS, Azure, or Google Cloud AI/ML certifications are preferred.

Interested consultants send CV to