Autodesk
Autodesk

61 Autodesk Machine Learning Intern Jobs Hiring Near You

What we're looking for At GPTZero, we ensure that machine learning models are created for the ... Past intern projects have been the focus of demos to VCs and state-level policy leaders.

What we're looking for At GPTZero, we ensure that machine learning models are created for the ... Past intern projects have been the focus of demos to VCs and state-level policy leaders.

POSITION SUMMARY As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer ...

What we're looking for At GPTZero, we ensure that machine learning models are created for the ... Past intern projects have been the focus of demos to VCs and state-level policy leaders.

Develop and improve machine learning models for Ads ranking and recommendation systems * Design and build features for ranking algorithms using large-scale datasets * Process and analyze billions of ...

Machine Learning Intern (R&D) Location: 5-days in NY office Job Type: Full time (June 15 - Aug 14, 2026) Job Reports To: Director of AI Salary Range: $30.00-$35.00/hr. About Jaan Health/Phamily Jaan ...

Machine Learning Intern (R&D) Location: 5-days in NY office Job Type: Full time (June 15 - Aug 14, 2026) Job Reports To: Director of AI Salary Range: $30.00-$35.00/hr. About Jaan Health/Phamily Jaan ...

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

next page

Showing results 1-20

Autodesk Jobs Information

What are the key skills and qualifications needed to thrive as a Machine Learning Intern, and why are they important?

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What types of projects do Machine Learning Interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What does a Machine Learning Intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

What is it like to work at Autodesk?

Autodesk is a company that values innovation, creativity, and collaboration, fostering a culture that encourages employees to think outside the box and push the boundaries of technology.

The company has a diverse range of teams, including software developers, designers, and engineers, working together to create cutting-edge products and solutions for industries such as architecture, engineering, and construction. Autodesk's offices often feature open workspaces, collaborative areas, and access to the latest technology, allowing employees to work efficiently and effectively.

Working at Autodesk may appeal to candidates who are passionate about technology, design, and innovation, and who are looking for a dynamic and challenging work environment that offers opportunities for growth and development in a rapidly evolving industry.
Infographic showing various Machine Learning Intern job openings at Autodesk in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 53% Physical, 1% Hybrid, and 46% Remote job distribution.
Senior Machine Engineer, ML Systems and Infrastructure

Senior Machine Engineer, ML Systems and Infrastructure

Autodesk

Delaware, OH • Remote

$99.20K - $135.70K/yr

Full-time

Posted 22 days ago


Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

5th of 183 rated software companies


Job description

Job Requisition ID #

26WD98118

POSITION OVERVIEW

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter.

Autodesk is seeking a Senior ML Engineer, ML Systems and Infrastructure to design and scale the systems that enable machine learning across research and product development. You will help build the infrastructure behind large-scale data pipelines, distributed training systems, evaluation frameworks, and production ML workflows that support foundation models and ML-powered product features.

This role is ideal for an engineer who is deeply interested in scalable systems and production-grade ML infrastructure. You will operate independently across multiple parts of the stack and help define strong engineering practices for reliability, performance, and maintainability.

This role is fully remote-friendly, with team members distributed across the US and Canada.

Location: US or Canada Remote, East Coast

RESPONSIBILITIES

  • Design and build scalable systems for ML training, evaluation, deployment, and monitoring

  • Develop and improve data pipelines that process large-scale structured and semi-structured technical datasets

  • Optimize distributed workflows for performance, reliability, resource utilization, and cost efficiency

  • Build platform capabilities such as experiment tracking, model versioning, checkpointing, reproducibility, and observability

  • Contribute to model deployment, inference services, and production monitoring workflows

  • Improve data quality, lineage, provenance, and operational transparency across ML pipelines

  • Contribute to architecture and design discussions across the team

  • Identify and resolve bottlenecks in data, compute, orchestration, and observability layers

  • Mentor engineers through code reviews, design guidance, and knowledge sharing

  • Collaborate closely with researchers, product engineers, and platform partners to turn ML workflows into robust engineering systems

MINIMUM QUALIFICATIONS

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent industry experience

  • At least 3 to 4 years of industry experience building and operating production software, ML systems, distributed infrastructure, or large-scale data pipelines

  • Strong experience in software engineering, distributed systems, backend systems, or ML infrastructure

  • Strong proficiency in Python and experience delivering production-quality systems

  • Experience designing and operating scalable data or compute pipelines

  • Experience with cloud platforms such as AWS, Azure, or GCP

  • Familiarity with containers, CI/CD, observability, and release quality practices

  • Ability to independently drive technical execution on complex work with limited oversight

PREFERRED QUALIFICATIONS

  • Experience building data pipelines for large-scale structured and semi-structured technical datasets

  • Experience with data lineage, provenance, governance, and responsible data usage in ML systems

  • Experience with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms

  • Experience with model deployment, inference services, monitoring, and observability for production ML systems

  • Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data

  • Experience with distributed ML frameworks such as PyTorch, Lightning, DeepSpeed, FSDP, Megatron, or similar

  • Familiarity with AEC workflows, design data, BIM/CAD formats, or Autodesk products

THE IDEAL CANDIDATE

  • Thinks like a systems engineer and executes like a strong software developer

  • Can balance short-term delivery with long-term platform health

  • Brings strong technical judgment and ownership

  • Improves team effectiveness through mentoring and engineering rigor

  • Enjoys solving scaling, performance, and reliability challenges

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.

Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). If you have any questions or require support, contact Autodesk Careers.

Autodesk logo

About Autodesk

Sourced by ZipRecruiter

Autodesk is changing how the world is designed and made. Our technology spans architecture, engineering, construction, product design, manufacturing, media, and entertainment, empowering innovators everywhere to solve challenges big and small. From greener buildings to smarter products to more mesmerizing blockbusters, Autodesk software helps our customers to design and make a better world for all. For more information visit autodesk.com or follow @autodesk.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Rafael, CA, US

Year founded

1982