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Computational Intelligence Jobs (NOW HIRING)

Advances in big chemical data, massive computing power, artificial intelligence, and molecular ... Own computational theoretical chemistry programs across therapeutic modalities, disease targets ...

Much of Kitware's work involves applying state-of-the-art computational imaging and artificial intelligence approaches to dynamic, real-world problems. You will have the opportunity to contribute ...

Much of Kitware's work involves applying state-of-the-art computational imaging and artificial intelligence approaches to dynamic, real-world problems. You will have the opportunity to contribute ...

Computational Protein Designer

San Francisco, CA · On-site

$24.25 - $29.50/hr

This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. Using your blend of computational expertise ...

Advances in big chemical data, massive computing power, artificial intelligence, and molecular ... Own computational theoretical chemistry programs across therapeutic modalities, disease targets ...

Advances in big chemical data, massive computing power, artificial intelligence, and molecular ... Own computational chemistry programs across therapeutic modalities, disease targets, and ...

Advances in big chemical data, massive computing power, artificial intelligence, and molecular ... Own computational theoretical chemistry programs across therapeutic modalities, disease targets ...

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Computational Intelligence information

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$11K

$100.6K

$133K

How much do computational intelligence jobs pay per year?

As of Jul 10, 2026, the average yearly pay for computational intelligence in the United States is $100,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,500.00 and $132,500.00 per year, depending on experience, location, and employer.

What is computational intelligence?

Computational intelligence is a field of artificial intelligence that focuses on developing algorithms and systems that can learn, adapt, and solve complex problems without explicit human programming. It typically includes techniques such as neural networks, fuzzy systems, evolutionary computation, and swarm intelligence. These methods are inspired by natural processes and are used in various applications like pattern recognition, optimization, and data analysis. Computational intelligence is widely used in industries ranging from finance to robotics.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior researcher, lead data scientist, or executive role, often requiring advanced skills in machine learning, deep learning, and programming. Such roles usually involve significant responsibilities, leadership, and expertise, and may be found in large tech companies or specialized AI firms with competitive compensation packages. These positions often demand advanced degrees, extensive experience, and a strong track record of innovation in AI development.

What are the key skills and qualifications needed to thrive as a Computational Intelligence Specialist, and why are they important?

A Computational Intelligence Specialist typically requires strong expertise in mathematics, programming (often Python or MATLAB), and a solid background in areas like machine learning, neural networks, and evolutionary algorithms, usually supported by a degree in computer science or a related field. Familiarity with technical tools such as TensorFlow, PyTorch, MATLAB, and data processing platforms is essential, along with relevant certifications or specialized coursework. Analytical thinking, creativity, and effective problem-solving abilities help professionals excel in developing innovative solutions and collaborating with multidisciplinary teams. These skills are vital for designing intelligent systems that can tackle complex, real-world problems efficiently and accurately.

Which 3 jobs will survive AI?

Computational intelligence professionals, data scientists, and AI specialists are likely to continue thriving as their roles involve designing, developing, and managing AI systems that require advanced analytical skills and domain expertise. These jobs demand critical thinking, creativity, and understanding of complex algorithms, making them less susceptible to full automation. Continuous learning and staying updated with new tools and techniques are essential for long-term job security in this field.

What jobs in the US pay 300,000 a year?

In the field of computational intelligence, senior roles such as machine learning engineers, data science directors, and AI research leads can earn $300,000 or more annually, especially with extensive experience, advanced degrees, and expertise in deep learning, neural networks, and big data tools. These positions often require strong programming skills, advanced certifications, and leadership responsibilities within tech companies or research institutions.

What are some common challenges faced by professionals working in Computational Intelligence, and how can they be addressed?

Professionals in Computational Intelligence often encounter challenges such as handling large and complex datasets, ensuring the interpretability of models, and keeping up with rapid advancements in algorithms and technology. Addressing these requires strong collaboration with domain experts, continuous learning through research and professional development, and applying best practices in data management and model validation. Effective teamwork and clear communication are essential, as projects frequently involve cross-functional teams including data scientists, engineers, and stakeholders from various disciplines.

What is the difference between Computational Intelligence vs Data Scientist?

AspectComputational IntelligenceData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; knowledge of machine learning, neural networksDegree in Statistics, Computer Science, or related fields; expertise in data analysis, programming
Work EnvironmentResearch labs, AI development teams, academiaBusiness environments, analytics teams, tech companies
Industry UsageAI research, pattern recognition, optimization problemsData analysis, predictive modeling, business insights

Computational Intelligence focuses on developing algorithms that mimic human decision-making and problem-solving, often in research or AI development settings. Data Scientists analyze large datasets to extract actionable insights for business decisions. While both roles require programming and analytical skills, Computational Intelligence emphasizes AI algorithm creation, whereas Data Scientists focus on data analysis and visualization.

What are the highest paying AI jobs?

High-paying AI jobs for computational intelligence professionals include roles such as AI research scientist, machine learning engineer, and data scientist, often requiring advanced degrees and expertise in deep learning, neural networks, and programming languages like Python. Salaries can exceed $150,000 annually, especially in tech hubs or with specialized skills and certifications. Senior positions or roles in industries like finance, healthcare, and autonomous systems tend to offer the highest compensation.
More about Computational Intelligence jobs
Infographic showing various Computational Intelligence job openings in the United States as of July 2026, with employment types broken down into 2% Internship, 71% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 70% Physical, 1% Hybrid, and 29% Remote job distribution, with an average salary of $100,573 per year, or $48.4 per hour.
Principal Computational Engineer, 3D CAD & Geometric Intelligence

Principal Computational Engineer, 3D CAD & Geometric Intelligence

Xometry

North Bethesda, MD

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


Job description

Xometry is seeking a Principal Computational Engineer to set the multi-year technical direction for our 3D geometry and Design for Manufacturability (DFM) platform. You will be the senior individual contributor in this domain, owning the architecture that turns every customer-uploaded CAD model into a manufacturable, priced, and routed part across CNC, sheet metal, additive, injection molding, casting, and finishing processes. This role also serves as the technical architect for one of Xometry's highest-leverage strategic initiatives: the embedded DFM AI + IQE integration with our partner. You will lead the integration of Xometry's proprietary computational geometry and AI directly into the partner's industrial software ecosystem - including Solid Edge, NX, Designcenter, and Teamcenter - integrated within the native DesignCenter environment to deliver real-time manufacturability feedback and pricing insights. The goal is a "science fiction speed" design-to-source digital thread from ideation to physical parts, with no export, no round-trip, and no translation loss. This is a hands-on role. You will write production C++ and Python that ships to millions of quotes per year, define the kernel and toolchain strategy, publish or patent novel methods where they create durable advantage, and raise the technical bar of the team through mentorship, design review, and hiring. The role requires demonstrated mastery of computational geometry, geometric modeling kernels, and the messy reality of consuming arbitrary customer CAD - STEP, IGES, X_T, JT, SLDPRT, CATPart, and DXF - at scale.

Responsibilities

  • Technical Vision & Roadmap: Own and drive a multi-year technical roadmap for Xometry's geometric reasoning stack - B-Rep ingestion and healing, feature recognition, DFM analysis, sub-process routing, geometric pricing signals, and downstream CAM/CAE integration - balancing research ambition with disciplined business value delivery.
  • Partnership Integration (DFM AI + IQE): Serve as the technical architect for the embedded DFM AI + IQE track inside the partner's ecosystem. Lead the integration of Xometry's geometric and AI capabilities directly into Solid Edge, NX, Designcenter, and Teamcenter, operating directly on native 3D geometry through the Parasolid kernel. Define the integration architecture, the geometry contract between the two systems, the precision and latency budgets required for in-CAD real-time feedback, and the long-term roadmap for an end-to-end digital thread from designer intent to manufactured part.
  • Geometric Kernel Architecture: Architect and personally implement the hardest components of the geometric kernel layer - robust intersection, offset, Boolean, projection, and trimming operations on NURBS curves and surfaces - plus the resilience layer that absorbs malformed CAD that arrives in the wild. Establish precision, robustness, and performance contracts (floating-point error budgets, predicate selection, tolerancing, numerical stability) that the rest of engineering builds on top of.
  • DFM & Sub-Process Intelligence: Drive the methodology for combining classical computational geometry (B-Rep traversal, parametric surface analysis, medial axis, geodesic distance, curvature analysis) with modern learning-based approaches (graph neural networks on B-Reps, point-cloud and voxel encoders, differentiable geometry, neural implicit representations) to detect manufacturability risk across 12+ CNC sub-processes and the broader process catalog.
  • Research-to-Production Translation: Translate research from computational geometry, computer-aided geometric design, and computational fabrication into shipped systems. Publish, patent, or open-source where doing so strengthens recruiting, partnerships, or the platform itself.
  • Technical Leadership & Standards: Provide technical leadership across geometry, ML, and platform teams. Lead design reviews, define the technical interview bar, and partner with engineering leadership on hiring, calibration, and IC-track career progression. Mentor Staff, Senior, and mid-level engineers.
  • Cross-Functional Leadership: Partner with Product, Manufacturing Engineering, Pricing, and Operations leadership to translate business outcomes (margin, lead time, yield, defect rate) into precisely specified geometric and algorithmic problems. Influence roadmaps, priorities, and resourcing across partner teams.
  • External Representation: Represent Xometry externally - conferences, standards bodies, academic collaborations, technical reviews, and customer engagements - as the recognized technical authority for our DFM and geometry platform.

What You'll Bring to Xometry

  • Experience & Education: M.S. or PhD in applied mathematics, computer science, mechanical engineering, computational physics, or a closely related field. Typically 12+ years of progressive experience applying computational methods to geometry, CAD/CAE, or simulation problems, with a demonstrable record of shipped algorithms in commercial or production systems. PhD with 8+ years of relevant industry experience is equivalent.
  • Geometric Modeling Mastery: Deep expertise across the geometric modeling stack - analytical geometry, parametric and free-form geometry (NURBS, etc.), trimmed surfaces, B-Rep topology, geometry healing and repair, robust predicates, and high-performance spatial data structures.
  • Kernel & CAD Interoperability: Hands-on experience with one or more commercial or open geometric kernels - Parasolid, ACIS, CGM, Granite, ShapeManager, Open CASCADE / pythonOCC - including a working understanding of where each kernel fails on real-world inputs and how to compensate. Strong working knowledge of CAD interchange and translation: STEP (AP203/AP214/AP242), IGES, JT, Parasolid XT, native CATIA / NX / Creo / SolidWorks formats, DXF, and HOOPS Exchange / PRC.
  • Technical Mastery: Expert-level C++ (C++14/17/20) with modern build systems (CMake), debugging (GDB, sanitizers), profiling, and binding generation (SWIG, pybind11). Strong Python for tooling, prototyping, and ML integration. Comfort with cloud platforms (AWS) for large-scale geometry processing and model training. Experiences or exposures of using code generation tools (e.g. Claude) with geometry engines. Ability to work in a large computational geometry codebase involving C++ and Python (numpy, numba) code.
  • Mathematical Rigor: Rigorous grounding in linear algebra, multivariable and differential calculus, numerical methods, differential equations, and floating-point error analysis. Comfort with differential geometry and topology as it applies to surface and curve modeling.
  • Recognized Track Record: Demonstrable record of research-to-production translation: peer-reviewed publications, issued patents, significant open-source contributions, or shipped commercial capabilities that you can point to and explain end-to-end.
  • AI/ML Fluency: Familiarity with ML/AI methods relevant to geometry - graph neural networks on B-Reps (BRepGAT, BRepFormer, AAGNet, UV-Net), point-cloud / voxel / SDF encoders, neural implicit representations, NURBS-aware learning - and clear judgment about when classical methods beat learned ones.
  • Manufacturing Domain Fluency: Familiarity with industry standards (ISO, ASME Y14.5, GD&T) and a working command of manufacturing processes (subtractive, additive, formative, finishing) and materials science sufficient to converse credibly with senior manufacturing engineers and partner engineers.
  • Leadership: Track record of mentoring and elevating Staff- and Senior-level engineers. Able to set technical direction by influence rather than mandate, and to align executives and cross-functional partners around ambitious scientific directions.
  • ITAR Compliance: Must be a US Citizen or Green Card holder (ITAR).

Qualifications

  • Partner Ecosystem Experience: Prior development experience inside the partner's stack - Parasolid kernel programming, NX Open / NX Customization, Solid Edge API, Teamcenter integration, or Designcenter / Mendix-based workflow development.
  • Published Research: PhD with a published thesis or sustained publication record in computational geometry, geometric modeling, computer-aided geometric design (CAGD), computational fabrication, isogeometric analysis, or computational dynamics.
  • Open-Source Authorship: Authorship of, or substantial contribution to, a recognized open-source geometric modeling library, kernel, or framework (e.g., NURBS / B-spline
    modeling frameworks, mesh generation toolkits, CAD interoperability libraries).
  • Industry Pedigree: Experience inside a CAD vendor, kernel vendor, simulation vendor, or vertically integrated manufacturing platform - Dassault Systemes, PTC, Autodesk, Onshape, Shapr3D, ANSYS, Altair, Desktop Metal, Markforged, Align Technology, ConforMIS, or comparable.
  • Scale: Designed and operated geometry algorithms at large scale - cloud compute, distributed geometry processing, GPU-accelerated computational geometry, parallel meshing, or geometry serving behind a real-time API.
  • Hiring & Calibration: Experience hiring, calibrating, and growing computational-geometry talent - a domain where the global talent pool is small and the hiring bar is notoriously difficult to set.

What Success Looks Like in 12 Months

  • The Partner DFM AI + IQE integration is in production inside the partner's ecosystem with measurable adoption, in-CAD latency contracts being met, and a clear roadmap for expanding the digital thread across additional processes and partner surfaces. 
  • The geometric reasoning stack has a coherent, documented architecture with explicit precision, robustness, and latency contracts; new sub-processes and DFM rules plug in without bespoke rewrites. 
  • DFM coverage spans 12+ CNC sub-processes plus the broader process catalog, with per-sub-process precision/recall measured and on a known improvement trajectory. 
  • At least one piece of methodology has been published, patented, or open-sourced in a way that strengthens Xometry's recruiting and external technical brand.
  • Two to three Staff and Senior engineers can credibly cite you as the reason they leveled up.

The estimated base salary range for new hires into this role is $200,000-$230,000.00 annually + commission depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

#LI-Hybrid


Xometry logo

About Xometry

Sourced by ZipRecruiter

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Industry

Software development

Company size

501 - 1,000 Employees

Headquarters location

Gaithersburg, MD, US

Year founded

2013