Evergreen - AI Engineer, AI FDE
Databricks4 days ago
Bengaluru, IndiaSenior
Responsibilities
- Develop LLM solutions for customer data, including RAG architectures, natural-language querying of structured data, agents, and content generation.
- Build, scale, optimize, and productionize customer data science and machine learning workloads across multiple domains.
- Apply MLOps practices to production machine learning deployments.
- Advise customer data teams on data science architecture, tooling, and best practices.
- Present technical work at conferences such as Data+AI Summit.
- Provide technical mentorship to the Databricks ML subject matter expert community.
- Collaborate with product and engineering teams to define priorities and influence the product roadmap.
Requirements
- 5+ years of hands-on industry data science experience.
- Experience building generative AI applications involving RAG, agents, text-to-SQL, fine-tuning, and LLM deployment.
- Experience with Hugging Face, LangChain, and OpenAI.
- Experience using machine learning and data science tools including pandas, scikit-learn, and TensorFlow or PyTorch.
- Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
- Graduate degree in a quantitative discipline such as Computer Science, Engineering, Statistics, or Operations Research, or equivalent practical experience.
- Experience communicating or teaching technical concepts to technical and non-technical audiences.
- Preferred experience with Databricks and Apache Spark for large-scale distributed datasets.
- Passion for collaboration, lifelong learning, and driving business value through machine learning.
Benefits
- Remote work is available.
- Comprehensive benefits and perks are offered, with details varying by region.
Tech Stack
Categories
AI ApplicationsForward Deployed
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.