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Tool Development Engineer Jobs (NOW HIRING)

The Pennsylvania State University

Reverse Engineering, Vulnerability Research, Malware Analysis, or CNO Tool Development * Computer Networking Fundamentals, Windows, and *NIX Operating Systems, X86(64) and ARM or MIPS architectures

Lorven Technologies

AI Solution Development

Atlanta, GA · On-site

Collaborate with engineering teams to design MCP-based integrations and other integrations for internal tool development. * Enable agent-driven workflows that streamline engineering processes across ...

maysteel

Development Engineer

Allenton, WI · On-site

We are excited to add a Development Engineer to our on-site team in Allenton, WI. This role is ... This individual works with Project and Program Engineers, Tech Center and Tool Room team members as ...

Intel

Test Development Engineer

Phoenix, AZ

Mechanical design, mechanical testing, and/or test tool development and maintenance. * Experience with manufacturing process improvement and/or solving complex engineering problems. * Development ...

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Tool Development Engineer information

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$49K

$96.2K

$153.5K

How much do tool development engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for tool development engineer in the United States is $96,155.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,500.00 and $106,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Tool Development Engineer, and why are they important?

To thrive as a Tool Development Engineer, you need a solid background in engineering principles, programming languages (such as Python, C++, or Java), and a relevant degree in computer science, engineering, or a related field. Familiarity with CAD software, version control systems, and automation tools, as well as certifications in relevant frameworks, are typically expected. Strong problem-solving skills, attention to detail, and effective communication enable collaboration and innovative tool design. These competencies are crucial for developing efficient, reliable tools that optimize engineering workflows and support organizational productivity.

What are some common challenges faced by Tool Development Engineers when collaborating with cross-functional teams?

Tool Development Engineers often work closely with software developers, QA testers, and product managers to create and refine tools. A common challenge is balancing differing priorities, such as development speed versus tool robustness or user-friendliness. Effective communication and flexibility are key to understanding and addressing the unique needs of each team. Regular feedback sessions and clear documentation help ensure that the tools developed meet the evolving requirements of all stakeholders.

What are Tool Development Engineers?

Tool Development Engineers are professionals who design, develop, and maintain tools, software, or equipment used to optimize production processes or support engineering teams. Their responsibilities often include understanding user requirements, creating prototypes, testing tools, and improving existing solutions to enhance efficiency and quality. They work closely with manufacturing, software, or hardware teams, depending on the industry. Tool Development Engineers play a critical role in increasing productivity and ensuring the reliability of tools used in various technical environments.

What is the difference between Tool Development Engineer vs Manufacturing Engineer?

AspectTool Development EngineerManufacturing Engineer
Primary FocusDesigning, developing, and optimizing tools and equipment used in manufacturing processesPlanning, implementing, and improving manufacturing processes and workflows
Skills & CertificationsMechanical design, CAD, problem-solving, certifications like Six Sigma or LeanProcess engineering, project management, certifications like Six Sigma or Lean
Work EnvironmentDesign labs, manufacturing plants, R&D facilitiesFactories, production lines, plant floor
Industry UsageCommon in automotive, aerospace, electronics manufacturingWidely used across various manufacturing sectors including consumer goods and industrial equipment

While both roles support manufacturing operations, the Tool Development Engineer primarily focuses on creating and improving tools and equipment, whereas the Manufacturing Engineer concentrates on optimizing entire production processes. Understanding these distinctions helps in choosing the right career path or job search focus.

More about Tool Development Engineer jobs
What cities are hiring for Tool Development Engineer jobs? Cities with the most Tool Development Engineer job openings:
What states have the most Tool Development Engineer jobs? States with the most job openings for Tool Development Engineer jobs include:
What job categories do people searching Tool Development Engineer jobs look for? The top searched job categories for Tool Development Engineer jobs are:
Tool Development Engineer jobs near you
Infographic showing various Tool Development Engineer job openings in the United States as of May 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 100% In-person job distribution, with an average salary of $96,155 per year, or $46.2 per hour.
ML Software Tool Development Engineer

ML Software Tool Development Engineer

Cerebras Systems

Sunnyvale, CA • On-site

Full-time

Posted 10 days ago

Job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Responsibilities:
  • Lead the design and implementation of system-level debugging, validation, and observability platforms.
  • Develop automated systems for collecting and analyzing numerical, and execution anomalies.
  • Create visualization and analysis tools to enable efficient root-cause investigation.
  • Build frameworks for failure classification, regression detection, and anomaly monitoring.
  • Extend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation.
  • Improve system bring-up, low-level debug, and validation workflows.
  • Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.
  • Establish best practices for debuggability, reliability, and operational excellence.
  • Lead high-impact initiatives.
  • Support incident response and drive long-term corrective actions.

Qualifications:
  • Strong proficiency in C++ and Python, with a track record of building reliable, high-performance systems and tooling.
  • Demonstrated experience debugging complex hardware/software systems and driving issues to root cause.
  • Experience analyzing system-level data structures, execution graphs, or dependency networks for diagnostics and validation.
  • Proven ability to design and build intuitive visualization and analysis tools for complex technical data.
  • Experience with compiler internals, custom hardware interfaces, or low-level protocol design.
  • Strong written and verbal communication skills, with the ability to explain technical concepts to diverse stakeholders.
  • Ability to work independently and lead complex technical projects end-to-end.

Preferred Skills & Qualifications
  • Familiarity with machine learning training and inference pipelines, especially distributed training and large-model scaling.
  • Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.

Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we've reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
  1. Build a breakthrough AI platform beyond the constraints of the GPU.
  2. Publish and open source their cutting-edge AI research.
  3. Work on one of the fastest AI supercomputers in the world.
  4. Enjoy job stability with startup vitality.
  5. Our simple, non-corporate work culture that respects individual beliefs.

Read our blog: Five Reasons to Join Cerebras in 2026.
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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