Senior Machine Learning Engineer

Required skills

Extensive hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains. End-to-end exposure in model lifecycle development, including demonstrated experience deploying and maintaining ML models in production environments. Strong knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine-tuning LLMs for domain-specific enterprise applications. Experience with MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments. Worked with agentic frameworks and autonomous agent architectures. Proficiency in Python and modern software development practices (testing, code review, CI/CD). Preferred skills: Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models. Experience with model serving frameworks (vLLM, TensorRT, Ray). Experience with A/B testing and experimentation frameworks for AI features. Experience with model observability tools (LangSmith, W&B, MLflow). Responsibilities: Contribute to the architecture and take ownership of the design, development, and deployment of scalable Generative AI and Machine Learning systems into production environments. Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations, and deployments. Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering and RAG implementation. Build cutting-edge conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language. Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics. Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations. Optimise model inference pipelines for performance, cost, and scalability in production environments. Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour. Participate in code reviews, lead technical design discussions, and provide mentorship to junior and mid-level engineers. Seniority: Senior. Domain: AI, Machine Learning, Enterprise Software.