Senior AI/ML Developer

Position overview As a Senior ML Developer on the team, you will be responsible for leading/contributing to the design, analysis, and delivery of data-driven solutions to significant business challenges across dedicated RAG programs of work. Your horizontal expertise in testing, evaluation and causal inference in the vertical domain of user interaction with text outputs, Information Retrieval as a theoretical discipline as the enabling tool will drive end-to-end planning, POC-building, offline and online evaluation and pushing features into the hands of users. The Senior MLE will work to deliver ML-driven technical solutions to customer needs in our platform. Sr MLEs help in coordinating delivery as part of multi-disciplinary stakeholder teams. This role is hands-on, focusing on technical problem solving with the latest in NLP and ML technology. Responsibilities - Design and implement Machine Learning capabilities that improve Autodesk's RAG platforms - Perform statistical and data analysis and exploration to generate datasets for model training and development - Collaborate with other members of the team to reach better solutions, and to position our team at the cutting edge of technology and ML practice - Provide technical leadership and mentorship for less-experienced members of the team to deliver key ML-powered features for our Digital Customer Platform. - Partner with stakeholders, to solve important business objectives across a range of problems - Translate business requirements and objectives into problems that can be solved with a combination of Data, Statistics, and Machine Learning Minimum Qualifications - MS/M.Tech/M.Math/ or PhD in Computer Science, Statistics, Mathematics, Physics, Developer, Economics, Computational Linguistics or related fields - 3+ years of applicable work experience in ML - Hands-on experience of NLU and integrating traditional search techniques into RAG - Proficiency with the Python Machine Learning stack, e.g. Pandas, deep learning frameworks, traditional ML, probability calibration etc. - Knowledge of experimental design and analysis of results - Demonstrate experience with leading Machine Learning teams in deploying and improving ML features in production - Demonstrate experience working in cross-functional teams to deliver ML solutions in production