AI/ML engineer in distributed cloud

We are seeking a versatile and passionate AI to join our data science and engineering team. You will be instrumental in bridging the gap between data science research and production-ready applications, building scalable machine learning systems that drive business value. This role requires a strong balance of software engineering principles and ML expertise.

• Design, develop, and deploy end-to-end AI pipelines, focusing on integrating Large Language Models (LLMs) and Foundation Models into production environments.
• Work closely with stakeholders to transition AI prototypes and experimental agents into scalable, production-grade systems, implementing modern LLM Ops practices.
• Develop robust, efficient code using Python and frameworks such as LangChain, LlamaIndex, or AutoGPT, alongside traditional libraries like PyTorch or TensorFlow when needed.
• Implement advanced monitoring for AI applications, focusing on output quality, hallucination detection, and performance tracking (e.g., using RAGas or Arize Phoenix).
• Collaborate with Data Engineers to build efficient data pipelines for vector databases (Chroma, Pinecone, Weaviate) and optimize context retrieval for RAG.
• Stay at the forefront of the rapidly evolving Generative AI landscape, exploring new techniques in prompt engineering, fine-tuning, and agentic workflows.

• 3+ years as an AI Engineer, ML Developer, or Software Engineer with a focus on AI integration.
• Strong proficiency in Python (clean, production-ready code) and experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex).
• Practical experience with Generative AI, Prompt Engineering, and fine-tuning Foundation Models (OpenAI, Hugging Face, Anthropic).
• Knowledge of Vector DBs (e.g., Pinecone, Weaviate, Chroma) and proficiency in SQL for data handling.
• Experience deploying AI applications on Cloud platforms (Azure AI, Vertex AI, or AWS Bedrock) and managing the AI lifecycle (LLMOps).
• Familiarity with Docker and API development (FastAPI/Flask) to build scalable AI services.
• Ability to translate business needs into AI solutions and communicate technical logic to non-tech teams.
• Degree in Computer Science, Engineering, or a related quantitative field.
• Professional level of English (written and spoken).

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