Autodesk Inc. · Boston, MA

Research Engineer at Autodesk Inc. — Boston, MA

Full-timeBoston, MA$122,000–$219,010/yearPosted 2026-07-20Apply on Workday

Full job description

Job Requisition ID #

26WD97952

The Autodesk Research Team

Autodesk Research partners with academia, industry, and government to explore the future of design, engineering, and manufacturing. Our teams combine scientific rigor with creative exploration to transform ideas into technologies that empower people to make anything.

The Manufacturing Industry Futures team investigates how data, automation, artificial intelligence, and emerging technologies can improve the way physical products are designed,engineered, manufactured, and inspected.

Position Overview Autodesk Research is seeking a Research Engineer with a strong understanding of manufacturing processes and an interest in applying artificial intelligence, data-driven methods, and automation to real-world manufacturing challenges.

Based at the Autodesk Technology Center in Boston, you will design and run applied research experiments that connect digital models, manufacturing processes, physical equipment, production data, and intelligent software.

This role requires knowledge of how physical products are manufactured. You should understand the principles, constraints, inputs, outputs, and trade-offs of multiple manufacturing methods, such as machining, forming, casting, molding, joining, assembly, inspection, and additive manufacturing. Direct experience operating every type of equipment is not required, but you must be able to reason about manufacturing processes and work effectively with specialists who operate them.

You will also work with manufacturing and experimental data to investigate how AI can support areas such as process planning, parameter selection, simulation, quality, anomaly detection, workflow automation, and engineering decision-making.

You do not need to be a foundational AI researcher. However, you should have begun applying machine learning, generative AI, agentic systems, or other data-driven techniques to engineering, manufacturing, or physical systems.

This is not a pure software-development role, a robotics-only role, or a position focused exclusively on additive manufacturing. Robotics, software, and additive manufacturing may form part of the work, but successful candidates will bring broader knowledge of manufacturing processes and systems.

We support hybrid work, and you will work from our Boston, Massachusetts office.

What You Will Do

 Design, build, and run applied research experiments focused on manufacturing processes, systems, and technologies.  Develop experimental workflows connecting design, engineering, simulation, manufacturing, inspection, sensing, automation, and production data.  Apply AI and data-driven methods to manufacturing problems such as process planning, parameter optimization, anomaly detection, quality prediction, simulation feedback, workflow automation, and decision support.  Collect, structure, analyze, and interpret data from manufacturing processes, machines, sensors, simulations, inspections, and experiments.  Compare manufacturing methods and evaluate their process capabilities, limitations, material considerations, quality requirements, and production trade-offs.  Build research prototypes that integrate software, hardware, data, and physical manufacturing processes.  Plan and conduct experiments using appropriate research methods, controls, measurements, and evaluation criteria.  Evaluate emerging technologies, including AI, digital twins, simulation, machine perception, robotics, sensing, and industrial automation, within manufacturing contexts.  Work with Technology Center specialists to conduct experiments involving processes such as machining, metal fabrication, joining, molding, forming, additive manufacturing, assembly, and inspection.  Collaborate with Autodesk researchers, engineers, Technology Center staff, industry partners, and academic institutions.  Contribute to research projects from problem definition and literature review through experimentation, prototyping, analysis, validation, and implementation.  Translate research findings into prototypes, demonstrations, intellectual property, technical publications, tools, and scalable technologies.  Communicate findings clearly through documentation, presentations, demonstrations, and technical discussions.

Minimum Qualifications  Bachelor’s or Master’s degree in Manufacturing Engineering, Mechanical Engineering, Industrial Engineering, Materials Engineering, Computer Science, Robotics, or a related technical field.  Relevant experience in applied research, industrial research and development, manufacturing engineering, process engineering, or a related environment.  Demonstrated understanding of multiple manufacturing processes rather than experience limited to a single technology or process.  Ability to explain how manufacturing processes work, including relevant materials, process parameters, equipment, constraints, sources of variation, and quality considerations.  Understanding of manufacturing workflows from design and process planning through production, inspection, and feedback.  Experience planning, conducting, and evaluating technical experiments.  Experience working with manufacturing, machine, sensor, simulation, inspection, production, or other experimental datasets.  Ability to analyze data using appropriate statistical, computational, or visualization methods.

 Initial practical experience applying machine learning, generative AI, agentic workflows, or other AI-assisted methods to engineering, manufacturing, research, or physical systems.  Ability to prototype integrated systems involving software, data, hardware, sensors, equipment, or physical processes.  Programming experience sufficient to support data analysis, automation, experimentation, and prototype development.  Strong technical communication and collaboration skills.  Ability to work across disciplines and engage effectively with researchers, software engineers, manufacturing specialists, and industry partners. Preferred Qualifications  PhD in Manufacturing Engineering, Mechanical Engineering, Industrial Engineering, Materials Engineering, Computer Science, Robotics, or a related field.  Applied knowledge of several manufacturing process families, such as: o Machining and subtractive manufacturing o Forming and sheet-metal processes o Casting and molding o Welding, joining, and assembly o Additive manufacturing o Inspection, metrology, and quality control o Industrial automation and production systems  Experience applying machine learning or AI to manufacturing processes, production systems, simulation, quality, inspection, maintenance, or process optimization.  Experience with AI-assisted engineering workflows, agentic systems, MCP or similar toolchains, or AI-enabled automation.  Experience with physics-informed machine learning, surrogate modeling, optimization, or AI for physical systems.  Familiarity with design of experiments, statistical process control, uncertainty, process capability, or manufacturing-quality methods.  Experience integrating data from multiple sources, including machines, sensors, simulations, inspection systems, and engineering software.  Familiarity with digital twins, model-based engineering, manufacturing simulation, or process simulation.  Familiarity with industrial data standards and communication protocols such as MQTT, MTConnect, OPC UA, or related industrial IoT technologies.  Experience developing research prototypes or intellectual property that has transferred into an industrial or commercial setting.  Evidence of curiosity, research rigor, and the ability to work in areas where the technical path is not yet defined. Indicators of a Strong Fit You may be a strong fit for this role if you:  Can compare several manufacturing methods and explain when and why each would be used.

 Understand that manufacturing data must be interpreted in the context of materials, equipment, process parameters, tolerances, quality, and physical constraints.  Have conducted structured experiments and can explain how you formed a hypothesis, selected measurements, analyzed results, and determined whether an approach worked.  Have used AI or machine learning in a practical engineering or research project, even if AI has not been the primary focus of your career.  Are comfortable moving between research questions, data analysis, software prototypes, physical experiments, and technical discussions with manufacturing specialists.  Are motivated by manufacturing problems rather than by robotics, software, or AI in isolation. Candidates whose experience is primarily in pure software development, building- information modeling, architecture and construction, biomedical applications, robotics without broader manufacturing-process knowledge, or a single additive-manufacturing method may not have the manufacturing breadth required for this position.

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Salary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, we expect a starting base salary between $122,000 and $219,010. 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.

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