Autodesk

Senior Machine Learning Engineer

Bengaluru, India
Docker Azure Spark PyTorch Python Java Kubernetes Git AWS Machine Learning TensorFlow
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Description

Job Requisition ID #

24WD82867

Position Overview 

MLOps Engineers will be responsible for deploying, maintaining, monitoring, integrating, and testing machine learning capabilities in production. You will partner with multi-disciplinary teams such as Machine Learning Engineering, Front-End Engineering, Infrastructure Engineering, Data Operations on coordinating delivery of customer-facing features. Your work will contribute to strategic initiatives such as optimization of digital conversion metrics and development of Autodesk Assistant, an LLM-driven chatbot intended to answer customer inquiries.  Our team culture is built on collaboration, mutual support, and continuous learning. We emphasize an agile, hands-on, and technical approach at all levels of the team. As a group, we want to continuously improve our work as well as our knowledge of trends and techniques relevant to our areas. We encourage personal development and knowledge sharing. 

Responsibilities 

  • Model Deployment: Collaborate with data scientists to deploy machine learning models into production environments, ensuring scalability and reliability
  • Automation: Develop and maintain CI/CD pipelines to automate the deployment and testing of machine learning models
  • Monitoring and Maintenance: Implement monitoring solutions to track model performance and detect anomalies, ensuring models continue to deliver accurate results over time
  • Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to integrate machine learning solutions into applications and services
  • Security: Ensure the security and compliance of machine learning models and data throughout their lifecycle
  • Documentation: Create and maintain comprehensive documentation for model deployment processes, CI/CD pipelines, and infrastructure setups
  • Platform Mindset: Partner with internal platform team on the following tasks
  • Demonstrate experience with deploying and improving ML features in production
  • Demonstrate experience working in cross-functional teams to deliver ML solutions in production
  • Ensure best practices in version control, testing, and documentation for ML projects 
  • Provide technical leadership and mentorship for less-experienced members of the team

Minimum Qualifications 

Technical Skills: 

  • 5 to 8 yrs of experience in MLOps
  • Technical Proficiency: Strong understanding of machine learning concepts and familiarity with frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
  • Programming Skills: Proficiency in programming languages such as Python or Java
  • DevOps Knowledge: Familiarity with DevOps practices and tools, including Docker, Kubernetes, Jenkins, and Git
  • Cloud Computing: Experience with cloud platforms (AWS, Azure) and containerization technologies (Docker, Kubernetes) 
  • Pipelines: Proficiency in designing and implementing data pipelines using tools like Apache Airflow, Kubeflow, or MLflow
  • Best Practices: Strong understanding of software engineering best practices, including testing, code review, and documentation

Analytical Skills: 

  • Strong problem-solving abilities and attention to detail
  • Ability to analyze complex datasets and derive actionable insights
  • Experience with data visualization tools

  

Preferred Qualifications

  • Familiarity with Large Language Models, especially in the context of interactive dialog systems and chatbots (RAG, Generative AI, Conversational Agents) 
  • Experience deploying systems that use NLP or experience working with Conversational AI frameworks
  • Experience with managing infrastructure required for model training, testing, and deployment, including cloud services, databases, and container orchestration platforms
  • Experience with distributed computing frameworks like Apache Spark 
  • Familiarity with feature stores and experiment tracking tools 
  • Knowledge of data governance and ML model governance practices 
  • Experience with A/B testing and statistical analysis 

  

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Learn More

About Autodesk
Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers.

When you’re an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, we also have a significant emphasis on discretionary annual cash bonuses, commissions for sales roles, stock or long-term incentive cash grants, and a comprehensive benefits package.

Diversity & Belonging
We take pride in cultivating a culture of belonging and an equitable workplace where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging

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