
Senior Generative AI Engineer
5 hours ago
Title: Senior Generative AI Engineer (Databricks,Data Lake)
Location: 100% Remote
Job Type: Fulltime
Key Responsibilities
• Design and implement GenAI models (LLMs, multimodal, embeddings, and fine-tuning) for enterprise use cases.
• Architect and optimize data pipelines and workflows in Databricks for large-scale AI training and inference.
• Manage and maintain data lakes on Databricks, ensuring data quality, governance, and scalability for AI workloads.
• Collaborate with data scientists, ML engineers, and product teams to translate business problems into AI-driven solutions.
• Implement MLOps pipelines for model deployment, monitoring, and lifecycle management in Databricks.
• Explore and evaluate state-of-the-art GenAI techniques and integrate them into scalable architectures.
• Optimize performance, scalability, and cost-effectiveness of AI systems in cloud environments (AWS/Azure/GCP).
• Contribute to technical strategy, mentorship, and best practices in AI and data engineering.
Required Qualifications
• 8+ years of professional experience in AI/ML engineering, data engineering, or related roles.
• Strong expertise with Databricks platform, including:
o Databricks Workflows & Delta Lake
o Databricks ML Runtime & MLflow
o Databricks SQL
• Hands-on experience designing and managing data lakes at enterprise scale.
• Proficiency in Python (PySpark, Pandas, ML/AI libraries) and SQL.
• Solid background in Machine Learning, Deep Learning, and Generative AI frameworks (e.g., Hugging Face, LangChain, OpenAI APIs, TensorFlow, PyTorch).
• Experience with MLOps practices, CI/CD pipelines, and cloud-native deployments.
• Strong knowledge of cloud platforms (AWS, Azure, or GCP) and data services.
• Excellent problem-solving skills and ability to design scalable AI solutions for complex datasets.
Preferred Qualifications
• Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Machine Learning Professional).
• Experience with vector databases (Pinecone, Weaviate, FAISS, Chroma).
• Experience with fine-tuning LLMs and integrating RAG (Retrieval-Augmented Generation) pipelines.
• Background in data governance, lineage, and compliance in large-scale AI systems.
• Contributions to open-source AI/ML projects or publications in the AI community.
Thanks
Vijay
Vijay.kumar@ampstek.com
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