AI/ML Engineer Offline

We are looking for a highly skilled and hands-on AI Engineer to design, build, and optimize AI workflows and solutions. You will work with cutting-edge technologies, including Agentic AI, Retrieval-Augmented Generation (RAG), LLM/SLM fine-tuning, reinforcement learning, and other advanced AI techniques. The ideal candidate will have a strong technical background and a passion for creating scalable, real-world AI applications.

Key Responsibilities 
• Design and Develop AI Workflows: Build end-to-end workflows for AI-driven applications, integrating tools like LLMs, RAG, and Agentic AI for practical business solutions.
• Cataloging AI Solutions: Develop and maintain a catalog of AI models, datasets, and reusable components to streamline development.
• Retrieval-Augmented Generation (RAG): Design and implement RAG pipelines for knowledge-intensive tasks, combining LLMs with vector databases like Pinecone, Weaviate, or similar.
• LLM/SLM Fine-Tuning: Fine-tune pre-trained large and small language models to optimize them for specific business use cases. (Llamma, Bert, LoRa)
• Agentic AI: Build autonomous agents that can perform tasks such as reasoning, planning, and execution in dynamic environments.
• Reinforcement Learning: Develop and implement reinforcement learning strategies to enhance model performance in complex environments.
• Data Integration: Work closely with data engineering teams to ensure seamless integration of structured and unstructured data from diverse sources.
• AI Optimization: Enhance performance and scalability of models for production by optimizing inference pipelines and leveraging techniques like model quantization.
• AI System Monitoring: Design and deploy systems to monitor AI performance and identify areas for improvement in real-time.
• Collaboration and Innovation: Work cross-functionally with product, engineering, and data science teams to identify and solve complex problems using AI.
• Stay Updated: Keep up with the latest advancements in AI research and technology, integrating them into workflows where appropriate.

Skills and Qualifications Required: 
• Proven experience in developing and deploying AI solutions in production.
• Strong understanding of LLMs, including experience with fine-tuning and leveraging open-source frameworks (e.g., Hugging Face, LangChain).
• Hands-on experience with RAG workflows and vector databases.
• Familiarity with Agentic AI concepts, such as autonomous task execution and planning.
• Strong proficiency in Python and AI/ML frameworks like PyTorch or TensorFlow.
• Solid understanding of reinforcement learning and experience implementing RL algorithms.
• Experience working with cloud platforms (AWS, GCP, Azure) for scalable AI solutions.
• Strong knowledge of data pipelines, ETL processes, and working with large-scale datasets.
• Experience with MLOps tools and techniques, such as Docker, Kubernetes, and CI/CD for AI models.Preferred: • Knowledge of low-resource fine-tuning techniques (e.g., LoRA, adapters).
• Familiarity with prompt engineering and chaining techniques for LLMs.
• Experience with OpenAI API, Anthropic, Cohere, or similar platforms.
• Background in information retrieval systems and search engines.
• Prior experience with knowledge graphs and semantic search.
• Contributions to AI research papers or open-source projects.

Key Technologies • Python (with AI/ML libraries like Hugging Face, LangChain, PyTorch, TensorFlow).
• Vector Databases (Pinecone, Weaviate, Milvus, Qdrant).
• MLOps Tools (Docker, Kubernetes, MLflow, Airflow).
• Cloud Platforms (AWS, GCP, Azure).
• Large Language Models (GPT-4, Llama 2, Falcon, etc.).
• Reinforcement Learning Libraries (Stable-Baselines3, Ray RLlib).

What We Offer 
• Opportunity to work with cutting-edge AI technologies and shape the future of intelligent systems.
• A dynamic and innovative work environment that fosters creativity and growth.

We are partnering with AWS & GCP and have top-tier clients in the UK and USA, and we are looking for a permanent strategic role to be covered.