▷ [Immediate Start] Senior Machine Learning Operations Engineer

Job Description

Job Requisition ID #

25WD89404

Position Overview

TheMLOpsEngineering teamis afast-moving team combining software engineeringwith ML system deployment and operations.As an ML Ops Engineer on the team, you willbe responsible forautomating and simplifying machine learning workflows and deployments. ML Ops Engineers work to implement and deliverMLcapabilitiesto solve complex real-world problems and deliver value toourcustomers.These processes include model development, testing, integration, release, and infrastructure management.

Our team culture is built on collaboration, mutual support, and continuous learning. In this role, you will automateand standardize processes across the ML lifecycle, collaborating with Data Scientists, Software Engineers, and other cross-functional stakeholders. 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 and knowledge of trends and techniques relevant to our areas.

We strive for excellence and pursue it with personal development and knowledge sharing.

Responsibilities

- Design and implement streamlined end-to-end, continuous, and automated process of deploying, monitoring, andmaintainingversioned ML models, at scale

- Design and implement services, tests, and interfaces to supportMachine Learning capabilities that improve Autodesk's eCommerce & Customer platforms

- Design and implement data pipelines and automated workflows to operationalize data atdifferent stagesof the Machine Learning lifecycle

- Participate in technical design and solutionsdiscussions with other technical leaders and members of staff like Architects, Machine Learning Engineers, Data Engineers

- Lead and mentorother members of the team in reaching better solutions, and to position our team at thecutting edgeof technology and ML practice

- Deploy innovative solutions from non-production environments to production with an eye on scalability and observability

Minimum Qualifications

- BS orMS in Computer Science, Statistics, Engineering, Economics, or related field

- At least 5years of applicable work experienceinML Ops, DevOps, or related fields, with a strong understanding of machine learning workflows and best practices

- Proficiencyin programming languages such as Python and familiarity with ML frameworks like TensorFlow,PyTorch, or Scikit-Learn. Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) is essential

- Strong analytical and problem-solving skills, with the ability to troubleshoot complex issues in ML pipelines and production environments

Preferred Qualifications

- Familiarity withLarge Language Modelsand related concepts likeRAG, Generative AI, Conversational Agents, MCP

- Experience deploying systems that use NLP or experience working with Conversational AI frameworks

- SQL and experience with big data technology such as Hive, Presto, Glue,(Py)Spark, or Athena

- Experience with data pipelines andtheAWSML ecosystem

- Strong Software Engineering skills

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About Autodesk

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