Senior AI/ML Engineer - Generative AI & LLM Solutions
Role details
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Tech stack
Job description
We are looking for an experienced Senior AI/ML Engineer with a strong background in Generative AI and Large Language Models (LLMs) to join our team. In this role, you will design and implement advanced AI-driven solutions that enhance system engineering processes and customer interactions. You will work on cutting-edge projects that integrate Agentic AI, RAG pipelines, and scalable deployment strategies, collaborating with multidisciplinary teams and industry leaders to deliver impactful solutions. What You'll Do * Design and implement automated workflows and AI-driven solutions for complex business and engineering challenges. * Develop and prototype Generative AI applications, including digital engineering assistants and knowledge management tools. * Integrate LLMs into production environments, ensuring scalability, security, and performance. * Collaborate with research and engineering teams to identify opportunities for AI integration and provide methodological recommendations. * Mentor team members, share best practices, and present learnings to stakeholders. * Stay up to date with emerging AI trends and assess their potential impact on future projects.
Requirements
Do you have experience in gRPC?, Do you have a Master's degree?, Required Skills & Experience * Strong Python skills and hands-on experience with LLMs and Generative AI (OpenAI, Anthropic, Google Gemini, Hugging Face, etc.). * Expertise in prompt engineering, fine-tuning, and adapter-based methods. * Practical knowledge of RAG (Retrieval-Augmented Generation), embeddings, and vector databases (Pinecone, ChromaDB, Weaviate, Qdrant, pgvector). * Familiarity with agent frameworks (LangChain, LlamaIndex, Google ADK / Vertex AI Agent Builder). * Experience deploying AI models and services to production using Docker, CI/CD, and cloud platforms (GCP preferred; Azure or Databricks experience is a plus). * Strong understanding of system design, distributed systems, and AI evaluation frameworks. * Ability to communicate complex AI concepts to diverse stakeholders and work in multidisciplinary teams. Preferred Qualifications * Degree in Computer Science, Engineering, Data Science, or related field. * Knowledge of graph-based knowledge integration (GraphRAG) and scalable AI deployment strategies. * Experience with FastAPI, REST/gRPC, and exposing AI services via APIs.