Senior Machine Learning Engineer - AI

At Forrester were trusted to work on trailblazing mission critical problems that business and technology leaders face today. Were proud of our community of smart people and vibrant voices who come together to do whats right by our clients and each other. As a Senior Machine Learning Engineer this individual will be challenged to develop enterprise-grade advanced ML and NLP solutions powering Izola Forresters conversational AI chatbot. This individual will architect and optimize its multiagent framework establish robust answer quality observability and retriever optimization systems and deliver intelligent trustworthy and natural conversations while ensuring scalable production-ready ML systems that deliver exceptional user experiences.

This role emphasizes senior-level ownership of end-to-end production ML systems: designing building and operating scalable conversational AI capabilities rather than narrowly scoped model research.

Apply design and coding best practices in writing highly optimized scalable and maintainable code for ML systems.
Answer quality: Build and maintain answer quality monitoring pipelines using platforms like Arize and LangSmith and fine-tune in our retrieval-augmented generation (RAG) architecture to improve relevance and accuracy.
Research and apply cutting-edge generative AI NLP and reinforcement learning techniques to enhance Izolas conversational intelligence as requirements evolve.
Collaborate: Work closely with product design and engineering teams to deliver multiagent conversational experiences.
Ensure quality: Apply rigorous testing observability and performance optimization for Izolas production environment.

Five-plus years designing and building enterprisegrade cloudnative applications on public clouds (AWS preferred).
Four-plus years in ML engineering owning endtoend data pipelines for scalable AI systems (e.g. search recommendations).
Deep expertise in LLMpowered conversational systems and RAG architectures including multisource indexing and ingestion for semantic and keyword hybrid retrieval.
Proven experience in designing and operating multiagent systems using modern orchestration frameworks (e.g. Agno Google ADK).
Experience in integrating ML observability platforms (e.g. Advanced proficiency in Python and cloudnative development with production ownership in AWS environments.
Strong experience with MLOps practices and scalable ML architectures from experimentation to production deployment.
Experience with reinforcement learning for dialogue optimization and experimentation (A/B testing design of experiments).
Experience with voice technologies (speech-to-text and text-to-speech) for conversational AI.

Were a network of knowledge and experience leading to richer fuller careers. If you would like to discuss a reasonable accommodation please reach out to .

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Required Experience: