Senior Machine Learning Engineer

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. The Senior Machine Learning Engineer will lead the design and development of next-generation AI systems, focusing on enhancing contact center operations through advanced machine learning techniques.

Responsibilities:

• Lead the design and development of Cresta’s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches
• Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems
• Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models
• Improve reasoning, planning, and tool-use capabilities in real-world AI applications
• Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies
• Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns
• Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance
• Optimize AI systems for scalability, latency, security, and cost efficiency in production environments
• Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into Cresta’s platform
• Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta’s AI systems

Requirements:

• Bachelor's degree in Computer Science, Mathematics, or a related field; Master's or Ph.D. preferred
• 5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs
• Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems
• Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments
• Experience building and evaluating complex agentic or multi-step LLM workflows
• Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure
• Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability
• Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar