Machine Learning Operations Developer

Machine Learning Operations Developer - AI/ML Platform Join Autodesk as a Machine Learning Operations Developer to apply for the AI/ML Platform role. Position Overview Autodesk is seeking a skilled MLOps Engineer to join the AI/ML Platform team. This role ensures the smooth operationalization of machine learning models and the overall efficiency of the next-generation AI/ML platform used in developing machine learning and generative AI solutions. Responsibilities Operational Efficiency: Drive the operational excellence of the AI/ML Platform by implementing and optimizing MLOps practices. Deployment Automation: Design and implement automated deployment pipelines for machine learning models. Scalable Infrastructure: Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, and data processing. Monitoring and Logging: Develop and maintain robust monitoring and logging systems to track model performance, system health, and overall platform efficiency. Collaboration with Data Engineers: Work closely with data engineers to ensure efficient data pipelines for model training and validation. Version Control and Model Governance: Implement version control systems for machine learning models and contribute to model governance practices. Governance and Trust: Contribute to the implementation of robust model governance practices, version control systems, and adherence to compliance standards. Security and Compliance: Enforce security best practices and compliance standards in all aspects of MLOps. Continuous Improvement: Identify opportunities for process automation, optimization, and implement strategies to enhance the overall MLOps lifecycle. Troubleshooting and Incident Response: Play a key role in identifying and resolving operational issues, contributing to incident response and system recovery. Minimum Qualifications BS or MS in Computer Science or a related field. 5+ years of hands-on experience in DevOps and MLOps, with a focus on deploying and managing machine learning models in production environments. Proficiency in implementing Infrastructure as Code practices using tools such as Terraform or Ansible. Strong expertise in containerization technologies (Docker, Kubernetes) for orchestrating and scaling machine learning workloads. Demonstrated experience in setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines for machine learning projects. Strong scripting skills in Python, Bash, or similar languages for automating operational processes. Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) for tracking system and model performance. Understanding of security best practices in MLOps, including data encryption, access controls, and compliance standards. Excellent collaboration and communication skills, working effectively with cross-functional teams. Proven ability to troubleshoot and resolve complex operational issues in a timely manner. Preferred Qualifications Experience with cloud platforms, especially AWS or Azure, for deploying and managing machine learning infrastructure. Familiarity with databases and data storage solutions commonly used in MLOps, such as SQL, NoSQL, or data lakes. Exposure to popular machine learning frameworks (TensorFlow, PyTorch) and their integration into MLOps processes. Previous experience with collaboration tools like Git for version control and Jira for project management. Familiarity with Agile development methodologies and working in an iterative, collaborative environment. We are committed to providing a competitive compensation package and a comprehensive benefits package. Autodesk is an equal opportunities employer and welcomes applications from all qualified candidates. #J-18808-Ljbffr