Senior Machine Learning Engineer

Job Requisition ID #

25WD94218

The Growth Experience Technology Machine Learning Team (GET-ML) @Autodesk

The GET-ML Team is responsible for delivering Machine Learning Features that transform the customer experience for Sales, Marketing, and Customer Success functions at Autodesk. Our mission is to help customers accomplish their goals through intelligent conversation, search, personalization, and automation, using data, machine learning, and modern NLP techniques to deliver meaningful outcomes at scale.

One of the team's major focus areas is the Commerce and Support Assistant (CSA), an LLM-driven conversational platform that is deployed in production and supports real customer interactions today. Alongside this work, the team is expanding into multi-agent systems, intelligent orchestration, and other applied machine learning capabilities that extend beyond a single product or interaction pattern. Our work spans conversational question answering, retrieval and ranking, agent-driven workflows, query routing, evaluation and measurement, and the continuous improvement of ML-powered systems operating at scale.

We work in a collaborative and supportive environment that values strong machine learning fundamentals, thoughtful experimentation, and practical impact. Team members partner closely with ML engineers, MLOps, product managers, and business stakeholders, and we encourage continuous learning and discussion about emerging techniques and when they are appropriate to apply.

Position Overview

As a Senior Machine Learning Engineer, you will play a key role in designing, developing, and evolving machine learning systems that support conversational AI, search, multi-agent solutions, and intelligent automation on Autodesk's customer platforms. You will work end to end, from data exploration and hypothesis formation through modeling, experimentation, deployment, and iteration on systems used by real customers.

This role is designed for someone who enjoys working across the full machine learning lifecycle and who is motivated by applying modern techniques, including large language models, in a rigorous and measurable way. While conversational and retrieval-based systems are an important part of our platform, this role is not limited to assembling existing components. You will have opportunities to adapt and fine-tune models, explore representation learning and ranking approaches, experiment with agent-based architectures, and bring new ideas from the rapidly evolving ML landscape into production.

As a Senior Machine Learning Engineer, you will also help influence technical direction by sharing best practices, mentoring teammates, and contributing to how we design, evaluate, and operate machine learning systems at scale.

Our team strives for excellence in the theory and practice of Machine Learning. We encourage personal development and knowledge sharing.

This role is currently open to remote work. Candidates must be located near one of our hub locations to support occasional in-office collaboration.

Responsibilities

• Design and implement machine learning capabilities that improve Autodesk's customer-facing platforms, including conversational question answering, search and retrieval, agent-based workflows, and intelligent automation

• Train, adapt, and improve machine learning models, including classical ML models, deep learning models, and LLM-based systems, for real-world production use cases

• Perform statistical analysis and data exploration to generate datasets for model training, experimentation, and evaluation

• Translate business objectives and product requirements into problems that can be addressed using data, statistics, and machine learning

• Collaborate with other members of the team to reach better solutions, and to position our team at the cutting edge of technology and ML practice

• Work closely with engineers, MLOps, and product partners to deploy, monitor, and iterate on ML systems running at scale

• Provide technical leadership and mentorship to less experienced team members, supporting their growth and contributing to a strong team culture

• Contribute to improving evaluation practices, ML tooling, and the overall technical foundations of the team

Minimum Qualifications

• MS or PhD in Computer Science, Statistics, Engineering, Economics, or related field. We also welcome applicants from non-traditional ML backgrounds

• 3+ years of applicable work experience in ML

• Demonstrated experience applying machine learning techniques, including both classical ML and deep learning approaches, to real-world problems

• Proficiency with the Python machine learning stack, including tools such as Pandas, NumPy, and Scikit-learn

• Experience with at least one deep learning framework, such as PyTorch

• Knowledge of experimental design and analysis, including evaluating model performance and interpreting results

• Experience or strong interest in NLP, information retrieval, conversational AI, or LLM-based systems

• Ability to work effectively in cross-functional teams and collaborate with engineers, product partners, and other stakeholders

• Experience contributing to or supporting machine learning systems in production environments

Preferred Qualifications

• Experience working with Large Language Models, particularly in the context of RAG, conversational systems, question answering, or agent-based applications

• Exposure to fine-tuning or adapting LLMs or embedding models for domain-specific use cases

• Experience with information retrieval, learning-to-rank, recommender systems, or other NLP-driven applications

• Familiarity with search technologies such as OpenSearch, Elasticsearch, Lucene, or Solr

• Experience with data pipelines, model serving, or MLOps practices, especially in cloud environments such as AWS

• Advanced software engineering skills, including data structures, algorithms, and building maintainable production code?

The Ideal Candidate

• There is no single ideal profile for a candidate for this role. We encourage you to apply if you think you would add to our team's ability to deliver innovative ML, even if you don't meet every single criterion

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 - it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Benefits

From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting

Salary transparency

Salary is one part of Autodesk's competitive compensation package. For U.S.-based roles, we expect a starting base salary between $131,400 and $235,950. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Equal Employment Opportunity

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

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