Senior ML Engineer

Autodesk Autodesk · Enterprise · Bangalore, India

Senior ML Engineer at Autodesk's Growth and Experience Technology (GET) organization, focusing on building and deploying production-grade ML systems for personalization, recommendations, search, and generative AI across the customer journey. The role involves end-to-end ML lifecycle ownership, from data to deployment and monitoring, with a strong emphasis on scalable infrastructure and product partnership.

What you'd actually do

  1. Design, build, and deploy scalable machine learning systems across personalization, search, recommendations, and retrieval use cases
  2. Develop and evaluate models using robust experimentation frameworks and data-driven methodologies
  3. Own components of end-to-end ML pipelines, including feature engineering, model training, validation, deployment, and monitoring
  4. Write production-quality code and contribute to scalable, maintainable ML infrastructure
  5. Analyze large datasets to extract insights and translate business problems into well-defined ML tasks

Skills

Required

  • Python
  • PyTorch
  • TensorFlow
  • Scikit-learn
  • structured and/or unstructured large-scale datasets
  • software engineering best practices
  • version control
  • testing
  • CI/CD

Nice to have

  • MS or PhD
  • personalization
  • recommendation systems
  • search
  • ranking systems
  • Generative AI
  • LLM fine-tuning
  • prompt engineering
  • RAG systems
  • cloud platforms (AWS, GCP, Azure)
  • ML deployment frameworks
  • MLops tools
  • MLflow
  • Kubeflow
  • SageMaker
  • Vertex AI
  • experimentation platforms
  • A/B testing
  • online metrics evaluation
  • communicate technical concepts clearly

What the JD emphasized

  • production environments
  • end-to-end ML lifecycle
  • production-quality code
  • scalable, maintainable ML infrastructure
  • large-scale datasets
  • Generative AI
  • LLM fine-tuning
  • prompt engineering
  • RAG systems
  • ML systems at scale

Other signals

  • production-grade ML systems
  • personalization, recommendations, search
  • generative AI capabilities