Manager, Engineering AI ML

Job Description

Your opportunity We are seeking a hands-on Manager of Engineering (AI/ML) to lead our team of talented ML engineers, data scientists, and software engineers. As a key member of our engineering leadership team, you will drive the development and implementation of cutting-edge AI/ML solutions that power business operations, and drive innovation.This role requires a strong blend of technical leadership, strategic thinking, and effective operations skills Our Engineering Managers are a select group of technology leaders and mentors who shape the solutions we bring to the market and foster an inclusive environment that brings out the best in people. If you have a strong technical background and you are also a person with great mentoring skills and that knows how to collaborate with multiple teams to ship great software, we would like to hear from you. What you ll do Lead end to end design, development, and deployment of scalable AI/ML models and systems ensuring high performance, reliability, and maintainability. Coach team on AI/ML projects, resolving complex technical challenges and ensuring successful project delivery. Establish and refine robust MLOps practices for seamless model development, deployment, monitoring and retraining. Leverage Gen AI techstack including Langchain, LLM and RAG to build Gen AI solutions that solve business challenges. Use RAG models to combine data in documents with EDW to solve complex use cases and reduce time to insights. Lead collaborative efforts across teams to strategically incorporate GenAI and LLM technologies into the companys applications Drive the recruitment, training, and development of top-tier talent in the region. This role requires 10+ Years of overall experience 5+ years of experience leading engineering teams Bachelors or advanced degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree (Masters or Ph.D.) preferred. Proficiency in ML packages like Tensorflow, PyTorch, scikit-learn, and Spark ML. Deep understanding of AI/ML algorithms, frameworks, and technologies, with hands-on experience in building and deploying AI/ML models at scale. Strong knowledge of software engineering best practices, including agile development methodologies, code review processes, and continuous integration/continuous deployment (CI/CD) pipelines. Deep understanding of Generative AI (transformers, diffusion models, etc.), RAG techniques, NLP concepts, and programming (Python, etc.). History of getting things done in a distributed, large-scale, and fast-growing environment Bonus points if you have Experience in LangChain