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Remote Computational Design Jobs (NOW HIRING)

Chemify Ltd

Staff CADD Scientist

San Francisco, CA · On-site +1

San Francisco (hybrid) or fully remote from Boston / San Diego Travel: Regular travel to our ... Own the computational design approach on assigned programmes, from hit discovery through lead ...

Weekday AI

Computational CAD Engineer - OpenSCAD

Remote Become a part of our customer's team as a Computational CAD Engineer specializing in OpenSCAD, where your practical skills with OpenSCAD will drive the development of cutting-edge AI-enabled ...

Harvey Performance Company

Design Engineer

Rowley, MA · On-site +1

Develop and manage computational models and analysis tools in MATLAB to support performance ... This role is remote, with the expectation that candidates are located within a reasonable driving ...

Harvey Performance Company

Design Engineer

Gorham, ME · On-site +1

Develop and manage computational models and analysis tools in MATLAB to support performance ... This role is remote, with the expectation that candidates are located within a reasonable driving ...

Mercor

RF Circuit Design Expert - PhD

San Francisco, CA · On-site +1

$70 - $100/hr

Remote Commitment: 15-20 hours/week Role Responsibilities * Design graduate-level computational problems using domain-specific scientific software libraries. * Develop problems requiring ...

Higharc

Architecture Lead, Ready to Build

$56.50 - $77.50/hr

Familiarity with BIM platforms and computational design tools like Grasshopper or Dynamo Working at Higharc Higharc has been remote first since our founding in 2018. We offer flexible hours so you ...

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How much do remote computational design jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for remote computational design in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

How do remote computational designers typically collaborate with multidisciplinary teams to ensure project success?

Remote computational designers often work closely with architects, engineers, and software developers through digital collaboration tools such as BIM platforms, cloud-based modeling software, and video conferencing. Regular virtual meetings, shared digital workspaces, and clear documentation help maintain effective communication and project alignment. To overcome challenges posed by physical distance, it's important for remote designers to be proactive in updates, responsive to feedback, and adaptable to different time zones. This collaborative approach ensures that design intents are accurately translated into computational models and that all team members stay informed throughout the project lifecycle.

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

To thrive as a Remote Computational Designer, you need expertise in computational geometry, algorithm development, and digital modeling, usually backed by a degree in architecture, engineering, or a related field. Proficiency with tools such as Grasshopper, Rhino, Dynamo, and programming languages like Python or C# is essential, along with familiarity with collaboration platforms. Strong problem-solving, communication, and self-management skills help you excel in remote settings and interdisciplinary teams. These skills are crucial for creating innovative design solutions, efficiently collaborating across distances, and meeting complex project requirements.

What is remote computational design?

Remote computational design refers to the use of algorithms, programming, and digital tools to create and optimize design solutions while working from a location outside of a traditional office. Professionals in this field leverage software like Grasshopper, Rhino, or Autodesk Dynamo to automate and enhance the design process for architecture, engineering, or product development. Working remotely, these designers collaborate with teams and clients through digital communication platforms, enabling flexibility and global cooperation.
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Remote Computational Design jobs near you
Infographic showing various Remote Computational Design job openings in the United States as of June 2026, with employment types broken down into 17% Full Time, and 83% Part Time. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Staff CADD Scientist

Chemify Ltd

San Francisco, CA • On-site, Remote

Full-time

Posted 8 days ago

Job description

About Chemify:
Chemify is revolutionising chemistry. We are creating a future where the synthesis of previously unimaginable molecules, drugs, and materials is instantly accessible. By combining AI, robotics, and the world's largest continually expanding database of chemical programs, we are accelerating chemical discovery to improve quality of life and extend the reach of humanity.
Our Chemifarm facility in Glasgow operates a growing fleet of advanced robotic systems that automate synthesis, optimisation, and library generation. This gives our computational scientists something rare: a direct, high-throughput bridge from in silico design to physically synthesised molecules, closing the design-make-test loop at a pace conventional drug discovery organisations cannot match.
Location: San Francisco (hybrid) or fully remote from Boston / San Diego
Travel: Regular travel to our Glasgow HQ / Chemifarm
The Role
We are seeking a Staff CADD Scientist to drive computer-aided drug design on Chemify's commercial programmes and computational platform. You will sit at the centre of a cross-disciplinary team - computational chemists, in-house and partner medicinal chemists, AI researchers, data engineers, and automation scientists - and shape how structure, simulation, and machine learning translate into molecules we actually make.
Your work sits at the interface between Chemify's platform and our commercial partners' drug discovery programmes. You will design and prioritise molecules for synthesis, work directly with partner chemists on medicinal-chemistry strategy - turning computational proposals into physically-made compounds.
If you are energised by solving complex scientific problems at the intersection of chemistry, physics, and AI - and by seeing your designs synthesised and tested within days rather than months - we'd love to welcome you to our team.
Key Responsibilities
  • Own the computational design approach on assigned programmes, from hit discovery through lead optimisation; partner with in-house and customer chemists on MPO and translate SAR into actionable hypotheses across DMTL cycles.
  • Deploy and advance methods across the CADD stack - docking, pharmacophore, shape and 3D-similarity, MD, FEP, QSAR modelling - choosing the right blend of physics- and ML-based approaches for each programmes.
  • Communicate reasoning, trade-offs, and recommendations to partner chemists and project leads.
  • Help productionise CADD methods into a reproducible, API-first toolkit; partner with Infrastructure on cost-effective GPU/HPC workflows.
  • Mentor computational chemists and junior CADD scientists; partner with the Head of Advanced Machine Learning on hiring and growth; act as the scientific interface with customers on commercial projects.
  • Represent Chemify's CADD capability externally - publications, conferences, and partner engagements where appropriate.

About You
You are a rare hybrid: a deeply credible computational chemist who is equally comfortable reasoning protein-ligand interactions and shipping code that runs in production. You care about getting real molecules made, not only writing elegant methods.
We expect you to bring:
  • PhD (or equivalent experience) in Computational Chemistry, Structural Biology, Biophysics, Physics, or a closely related field, plus 8+ years of hands-on CADD experience in small-molecule drug discovery - including owning the computational strategy on active programmes.
  • Strong grounding in both structure- and ligand-based drug design - protein-ligand biophysics on one side, and pharmacophore, shape, and SAR-driven design on the other - with hands-on use of standard CADD stack (e.g. MOE, PyMOL, OpenMM / GROMACS / AMBER).
  • Familiarity with core drug discovery and medicinal chemistry principles - translating diverse assay readouts into design hypotheses - and a clear understanding of pharmacological principles to keep CADD output biologically relevant.
  • Working knowledge of modern deep learning for molecular design (GNNs, generative models, property prediction), and a clear sense of when these complement traditional CADD methods rather than replace them.
  • Strong Python and at least one core cheminformatics toolkit (e.g. RDKit, OpenEye); real experience inside the drug-discovery loop (SAR, MPO, DMTL cycles, lead optimisation, library enumeration); comfort with GPU-accelerated simulation and cloud/HPC workflows.
  • The ability to present computational reasoning to working chemists and partner scientists and a track record of technical leadership beyond your own projects.

Beneficial Skills
  • Hands-on experience with free energy perturbation (FEP+, OpenFE, or equivalent) in a production drug-discovery setting.
  • Practical use of generative chemistry methods (diffusion, autoregressive, RL-based design), including a clear-eyed view of their failure modes.
  • Familiarity with active learning, iterative DMTL design loops, and Bayesian optimisation applied to molecular design.
  • Experience building or integrating CADD tooling into API-first platforms (FastAPI, Docker, CI/CD), and proficiency in C/C++ / CUDA for high-performance computational chemistry.
  • A visible track record in the field - peer-reviewed publications, open-source contributions, or public projects that demonstrate your judgement on real CADD problems.

Why Join Chemify?
Impact:
You will directly shape the molecules Chemify designs and makes - at a company uniquely positioned to close the design-make-test loop through automated chemical synthesis at scale.
Autonomy:
Reporting to the Head of Advanced Machine Learning, you will own CADD strategy on your programmes, choose the methods and tools, and have meaningful influence over the computational platform that supports every project at Chemify.
Ambition:
We are a Series B deep-tech company investing in world-class infrastructure and tackling problems at the frontier of AI, robotics, and chemistry. You will have the resources, the data, and the mandate to do CADD in a way that isn't possible elsewhere.

Apply