Data Scientist / Gen AI Lead Consultantwith Generative AI, Agentic AI, Machine Learning

Job Title -Data Scientist / Gen AI Lead Consultant with Generative AI, Agentic AI, Machine Learning (ML) Location -Alpharetta, GA, Bridgewater, NJ, Charlotte, NC, Denver, CO, Hartford, CT, Houston, TX, New York, NY, Palm Beach, FL, Phoenix, AZ, Raleigh, NC, Richardson, TX, Sunnyvale, CA, Tampa, FL, Tempe, AZ, Washington, VA or is willing to relocate.

Type: Fulltime

Job Description:

Data Scientist / Gen AI Lead Consultant with Generative AI, Agentic AI, Machine Learning (ML), AI and Python experience. Ideal candidate is expected to have prior experience in end-to-end implementation of Gen AI and Agentic AI based solution, fine tuning large language models, Machine Learning models that includes identification of right problem, designing optimum solution, implementing using best in class practices and deploying the models to production. Will work in alignment with data strategy at various clients, using multiple technologies and platforms.
Required Data Scientist Qualifications:

• Bachelor s Degree or foreign equivalent will also consider three years of progressive experience in the specialty in lieu of every year of education.
• At least 8 years of Information Technology experience
• At least 4 years of hands-on GenAI / Agentic AI and data science with machine learning
• Strong proficiency in Python programming.
• Experience of deploying the Gen AI applications with one of the Agent Frameworks like LangGraph, AutoGen or Crew AI.
• Experience in deploying the Gen AI stack/services provided by various platforms such as AWS, Google Cloud Platform, Azure, IBM Watson
• Experience in Generative AI and working with multiple Large Language Models and implementing Advanced RAG based solutions.
• Experience in processing/ingesting unstructured data from PDFs, HTML, Image files, audio to text etc.
• Experience with Hybrid Retrieval, Semantic Chunking, Metadata Filtering and Vector Search Optimization
• Experience with Advanced LLM concepts like Prompt Compression, Fine-Tuning, Caching, etc.
• Experience working with multimodal models integrating image, text, or audio into GenAI workflows.
• Experience working with Vector Databases (such as FAISS, Pinecone, Weaviate, or Azure AI Search).
• Experience in Model evaluation tools like DeepEval, FMeval, RAGAS , Bedrock model evaluation, including human-in-the-loop feedback loops.
• Experience with LLMOps practices including prompt versioning, caching, observability, cost tracking, and production deployment of LLMs.
• Strong understanding of AI governance (like GDPR, explainability), data privacy, model safety (e.g., hallucination, toxicity, bias), and enterprise-grade compliance requirements.
• Experience with data gathering, data quality, system / microservices architecture, coding best practices
• Experience with Lean / Agile development methodologies
• This position may require travel, will involve close co-ordination with offshore teams

Preferred Data Scientist Qualifications:

• 4 years of hands-on experience with more than one programming language; Python, R, Scala, Java, SQL
• Hands-on experience with CI/CD pipelines and DevOps tools like Jenkins, GitHub Actions, or Terraform.
• Proficiency in NoSQL and SQL databases (PostgreSQL, MongoDB, CosmosDB, DynamoDB).
• Deep Learning experience with CNNs, RNN, LSTMs and the latest research trends
• Experience in Python AI/ML frameworks such as TensorFlow, PyTorch, or LangChain.
• Strong understanding and experience of LLM fine-tuning, local deployment of open-source models
• Proficiency in building RESTful APIs using FastAPI, Flask, or Django.
• Experience in Model evaluation tools like DeepEval, FMeval, RAGAS , Bedrock model evaluation.
• Experience with perception (e.g. computer vision), time series data (e.g. text analysis)
• Big Data Experience strongly preferred, HDFS, Hive, Spark, Scala
• Data visualization tools such as Tableau, Query languages such as SQL, Hive
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Exposure to Front -End / Full-Stack Integration (React / Angular, TypeScript, REST APIs, GraphQL, Event-Driven etc.)