Senior ML Engineer

Job Requisition ID #

26WD95860

Position Overview

We are looking for a Senior Machine Learning Engineer to join the ML team in Bangalore within Autodesk's Growth and Experience Technology (GET) organization. The GET ML team builds measurable AI solutions that power personalization, recommendations, search, and emerging generative AI capabilities across Autodesk's customer journey. As a Senior ML Engineer, you will play a key role in designing and delivering production-grade ML systems that directly impact Autodesk's go-to-market ecosystem. You will help define how machine learning powers personalized experiences for millions of Autodesk customers worldwide.

This role combines deep technical execution with strong product partnership. You will take ownership of complex ML initiatives-from problem framing and experimentation through production deployment-while collaborating closely with product, engineering, analytics, and research teams. You will contribute meaningfully to architectural decisions, raise the technical bar of the team, and help shape best practices for applied machine learning in Bangalore.

Autodesk follows a hybrid work model. You may work remotely or from an Autodesk office, with periodic travel as business needs require.

Responsibilities

• Design, build, and deploy scalable machine learning systems across personalization, search, recommendations, and retrieval use cases
• Develop and evaluate models using robust experimentation frameworks and data-driven methodologies
• Own components of end-to-end ML pipelines, including feature engineering, model training, validation, deployment, and monitoring
• Write production-quality code and contribute to scalable, maintainable ML infrastructure
• Analyze large datasets to extract insights and translate business problems into well-defined ML tasks
• Partner closely with product, design, engineering, and analytics teams to deliver solutions with measurable business impact
• Participate in code reviews, model reviews, and design discussions to uphold engineering excellence
• Contribute to documentation, knowledge sharing, and mentoring junior engineers where appropriate

• Bachelor's or master's Degree in a relevant field such as Computer Science, Data Science, Statistics, or a related quantitative discipline
• 4+ years of industry experience building and deploying machine learning systems in production environments
• Strong hands-on experience across the end-to-end ML lifecycle (data preparation, modeling, evaluation, deployment, monitoring)
• Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
• Experience working with structured and/or unstructured large-scale datasets
• Solid understanding of software engineering best practices (version control, testing, CI/CD)
• Collaborative mindset and ability to work effectively in a global team

• MS or PhD in a relevant field
• Experience with personalization, recommendation systems, search, or ranking systems
• Experience with Generative AI, LLM fine-tuning, prompt engineering, or RAG systems
• Experience building or operating ML systems at scale (cloud platforms such as AWS, GCP, or Azure)
• Experience with model deployment frameworks or MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI)
• Familiarity with experimentation platforms (A/B testing, online metrics evaluation)
• Ability to communicate technical concepts clearly to cross-functional stakeholders