Hi,
Hope you are doing well.
Please go through the following requirements and let me know with your updated resume if you are comfortable.
Job Title: Senior Engineer – AI/ML - Databricks
Location: King of Prussia, PA (Onsite) - Final round F2F interview
Duration: Long Term Contract
Job Description - We are seeking a for AI engineers having project experience of developing and deploying AI projects on Databricks and Mosaic AI. The ideal candidate will have a strong background in machine learning, distributed data processing, and will be a champion of the Databricks platform.
Responsibilities
- Generative AI: Experience with LLM-based solutions (LlamaIndex, LangChain, RAG pipelines, or similar frameworks). Ability to integrate GenAI and Agentic AI into business workflows.
- Design and implement end-to-end Generative AI solutions on Databricks, leveraging Unity Catalog, MLflow, Delta Lake, and Vector Search.
- Design, build, and deploy large-scale AI/ML models using the Databricks environment.
- Implement data validation, lineage, and monitoring using Delta Live Tables and Unity Catalog.
- Leverage Databricks’ data engineering workflows for feature engineering, model training, and evaluation.
- Optimize training pipelines for efficiency, scalability, and accuracy.
- Integrate AI models into production systems using APIs and microservices.
- Build reusable ML pipelines using Databricks Repos, MLflow, and Feature Store.
- Implement robust testing, monitoring, and retraining protocols for deployed models.
- Ensure adherence to compliance, security, and performance standards.
- Stay updated on advancements in AI frameworks, distributed computing, and Databricks platform updates.
Required Skills and Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
- Experience of developing and deploying AI projects on Databricks and Mosaic AI.
- Certified Databricks Certified Generative AI Engineer.
- Proven experience developing AI solutions on Databricks.
- Strong knowledge of Python, PySpark, MLflow, Spark, and Databricks Notebooks.
- Strong understanding and knowledge of Databricks platform features such as Unity Catalog, DLT, MosaicAI, Data Assets Bundles, etc.
- Experience with Transformer-based models, Generative AI, and Databricks pipelines.
- Proficiency in integrating AI models with cloud-native architectures (AWS, Azure, or GCP).
- Solid understanding of MLOps practices, Data Assets Bundles (CI/CD), and containerization (Docker, Kubernetes) on the Databricks Platform.
- Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).
- Strong problem-solving, analytical thinking, and communication skills .
Thanks
Sathish Korapati
Technical Recruiter
