About the job
Join us as a Senior Machine Learning Engineer to design, build, and deploy production-grade AI systems that power intelligent experiences across commercial and promotional activities. Lead the development of GenAI agents and predictive ML solutions, collaborating with cross-functional teams. Ideal for experienced professionals with strong AI/ML expertise and a background in enterprise-scale data.
Responsibilities
Design, build, and deploy production-grade AI systems, including GenAI agents, predictive ML, retrieval and reasoning systems, agent frameworks, tool calling, multi-agent workflows, APIs, and data pipelines, with a strong focus on quality, scalability, reliability, and performance.
Develop AI/ML solutions over large-scale structured and unstructured enterprise data, including evaluation frameworks and techniques to continuously improve accuracy and user experience.
Own solutions end-to-end, from architecture and experimentation through implementation, testing, deployment, monitoring, and continuous improvement.
Partner closely with product managers and collaborators to identify high-value problems and integrate AI capabilities into real-world sales and marketing workflows.
Identify and prototype emerging AI opportunities, turning new technologies and ideas into differentiated, production-ready capabilities.
Qualifications
Minimum
MS or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
5+ years of experience building and deploying machine learning, GenAI, NLP, retrieval, or related AI systems.
Strong understanding of modern LLM and agentic AI technologies, including RAG, tool/function calling, reasoning, evaluation, and context management.
Strong foundation in machine learning, predictive modeling, statistics, and techniques for working with large-scale structured and unstructured data.
Strong software engineering skills, including Python, data structures and algorithms, system design, testing, code quality, and production debugging.
Experience building production AI/ML services using technologies such as PyTorch, REST APIs, Docker, data/orchestration pipelines, and cloud platforms such as Azure or AWS.
Experience designing scalable and reliable AI systems and evaluating them across quality, latency, cost, and operational performance.
Excellent problem-solving and communication skills, with the ability to work effectively across technical and business teams in a fast-paced environment.
Preferred
No preferred qualifications listed.