Data Scientist

About the Role

Key Responsibilities

• Implement end-to-end Gen AI and Agentic AI solutions, including fine-tuning large language models.
• Identify 'right' problems and design 'optimum' solutions for AI projects.
• Deploy Gen AI applications using frameworks like Langgraph, Autogen, Crew AI.
• Deploy Gen AI stack/services on platforms such as AWS, GCP, Azure, IBM Watson.
• Work with multiple Large Language Models and implement advanced RAG-based solutions.
• Process and ingest unstructured data from PDFs, HTML, images, audio, etc.
• Gather data, ensure data quality, and follow system architecture and coding best practices.
• Collaborate with offshore teams and coordinate travel as required.

Requirements

• Bachelor's Degree or equivalent; three years of progressive experience in lieu of every year of education.
• At least 8 years of Information Technology experience.
• At least 4 years of hands-on experience with GenAI / Agentic AI and data science with machine learning.
• Strong proficiency in Python programming.
• Experience deploying Gen AI applications with frameworks like Langgraph, Autogen, Crew AI.
• Experience deploying Gen AI services on platforms such as AWS, GCP, Azure, IBM Watson.
• Experience working with multiple Large Language Models and implementing RAG-based solutions.
• Experience processing unstructured data from various sources.
• Experience with data gathering, data quality, system architecture, and coding best practices.
• Hands-on experience with Vector Databases such as FAISS, Pinecone, Weaviate, or Azure AI Search.
• Experience with Lean / Agile development methodologies.
• Willingness to travel and coordinate with offshore teams.
• Location flexibility in multiple US cities or willingness to relocate.

Nice to Have

• Experience with more than one programming language such as R, Scala, Java, SQL (4 years).
• Experience with CI/CD pipelines and DevOps tools like Jenkins, GitHub Actions, Terraform.
• Proficiency in NoSQL and SQL databases such as PostgreSQL, MongoDB, CosmosDB, DynamoDB.
• Deep Learning experience with CNNs, RNNs, LSTMs, and current research trends.
• Experience with Python AI/ML frameworks like TensorFlow, PyTorch, LangChain.
• Experience in fine-tuning LLMs and deploying open-source models locally.
• Proficiency in building RESTful APIs using FastAPI, Flask, or Django.
• Experience with model evaluation tools like DeepEval, FMeval, RAGAS, Bedrock.
• Experience with perception (computer vision) and time series data (text analysis).
• Big Data experience with HDFS, Hive, Spark, Scala.
• Data visualization skills with tools like Tableau and query languages like SQL, Hive.
• Good applied statistics skills such as distributions, statistical testing, and regression.

Benefits & Perks

• Medical/Dental/Vision/Life Insurance
• Long-term/Short-term Disability
• Health and Dependent Care Reimbursement Accounts
• Insurance (Accident, Critical Illness, Hospital Indemnity, Legal)
• 401(k) plan and contributions dependent on salary level
• Paid holidays plus Paid Time Off