Job description
Introduction
We are seeking a highly skilled and experienced Senior Data Scientist with deep expertise in Machine Learning, Deep Learning, and Generative AI. The ideal candidate will have a strong track record of delivering end-to-end data science solutions in production environments and hands-on experience with LLMs and Agentic AI frameworks. You will be responsible for driving AI/ML projects from ideation to deployment, collaborating with cross-functional teams, and ensuring scalable implementations.
Your role and responsibilities
- Lead end to end Databricks implementations covering data ingestion, ETL and ELT pipelines, Delta Lake architecture, feature engineering, MLflow based model development, deployment, and monitoring, and extend the platform with Databricks Agents and Databricks Apps to build governed, secure, and scalable AI driven applications for enterprise use cases.
- Execute end-to-end Data Science projects including data collection, preprocessing, feature engineering, modelling, evaluation, and deployment.
- Design and implement advanced Machine Learning algorithms (classification, regression, clustering, ensemble methods) and Natural Language Processing algorithms
- Develop and deploy Generative AI and LLM-based solutions using platforms like OpenAI, Hugging Face, and LLaMA, with Retrieval Augmented Generation RAG and advanced RAG patterns including hybrid search, vector databases, re ranking, prompt optimization, and context grounding for enterprise scale use cases.
- Apply Agentic AI frameworks such as LangChain, LangGraph, Crew AI, or Microsoft Semantic Kernel to design, orchestrate and govern multi agent workflows.
- Skilled in leveraging ML platforms, managed databases, web hosting services, and document AI tools for end-to-end solution development.
- Proficient in designing and deploying scalable machine learning solutions using cloud architectures, with hands-on experience in at least one major platform (Azure, AWS, GCP, or IBM Cloud).
- Collaborate with business stakeholders to define problem statements, deliver insights, and drive impact.
- Maintain reproducibility and version control using Git, GitHub
- Effectively communicate technical concepts and project outcomes to both technical and non-technical stakeholders.
Required education
Bachelor's Degree
Preferred education
Master's Degree
Required technical and professional expertise
- 7-9 years of hands-on experience in Data Science, Machine Learning, Deep Learning, and NLP in a production environment.
- 3+ years of applied experience in Generative AI and LLMs (e.g., OpenAI, LLama).
- Strong hands on experience in end to end Databricks implementation including data ingestion, ETL and ELT pipelines, Delta Lake, MLflow, and deployment of scalable analytics, machine learning, and AI applications.
- Proficiency in agentic AI development using frameworks like LangChain, LangGraph, or similar.
- Strong programming skills in Python and experience with ML/DL libraries
- Experience deploying models via REST APIs or web applications.
- Proficient in SQL for data extraction, transformation, and analysis.
- Experience working with large datasets, feature engineering, and data preprocessing pipelines.
- Solid understanding of model evaluation, cross-validation, and performance metrics.
- Experience in MLOps, including model testing, deployment pipelines, governance frameworks, and continuous monitoring for reliable and compliant machine learning operations.
- Experience with cloud ML pipelines and services (proficiency in at least one of Azure, AWS, GCP & IBM Cloud).
- Strong interpersonal and client communication skills.
Years of Experience:7-9
This job post has been translated by AI and may contain minor differences or errors.
