Senior Machine Learning Engineer Hybrid Contract We are seeking a highly skilled Senior Machine Learning Engineer with expertise in Generative AI to join our growing technology team. This role is focused on designing, developing, and deploying advanced AI solutions that leverage large language models (LLMs), Retrieval-Augmented Generation (RAG), and image generation technologies. Key Responsibilities: • Design and implement generative AI systems, including RAG pipelines and LLM-based applications using Azure OpenAI, Snowflake Cortex, and Azure Cognitive Search. • Fine-tune and optimize LLMs and SLMs using techniques such as supervised learning, reinforcement learning with human feedback (RLHF), and prompt tuning. • Develop and maintain CI/CD pipelines for AI workflows, ensuring scalability and reliability. • Integrate Snowflake’s native ML capabilities for data preparation, feature engineering, and inference. • Monitor model performance, including hallucination detection, drift monitoring, and feedback loop implementation. • Collaborate with cross-functional teams to translate business requirements into scalable AI solutions. • Maintain comprehensive documentation for model development, deployment, and prompt libraries. Qualifications: Required: • Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience). • 4–6 years of experience in machine learning, MLOps, or software development, including at least 1 year in generative AI or LLMs. • Proficiency in Python and experience with libraries such as LangChain, Hugging Face, and PyTorch. • Hands-on experience with Microsoft Azure (OpenAI, AzureML, Cognitive Search) and Snowflake (Snowpark, Cortex). • Strong understanding of RAG architectures, vector databases, and prompt engineering. • Familiarity with MLOps tools such as MLflow, Docker, Kubernetes, and GitHub Actions. Preferred: • Master’s degree in AI, Machine Learning, or Data Science. • Experience with RLHF, synthetic data generation, or human-in-the-loop systems. • Contributions to open-source LLM or RAG projects. • Experience building and maintaining Small Language Models (SLMs). • Strong communication skills and the ability to work effectively with both technical and non-technical stakeholders.