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Remote Computational Chemical Engineering Jobs (NOW HIRING)

Computational Materials Scientist

Woburn, MA · On-site +1

$180K - $200K/yr

D. in Mechanical Engineering, Materials Science, Chemical Engineering, or a closely related computational/physics field. * Core Simulation Expertise: Deep and extensive experience in atomistic ...

Staff Computational Biologist

Lexington, MA · On-site +1

$195K - $230K/yr

Our talented team of biologists, chemists and engineers, armed with advanced AI/ML tools, work ... Familiarity with the drug discovery and development process is a plus Remote Salary Range $165,750 ...

$86K - $129K/yr

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... A master's degree in an advanced degree in chemistry, chemical engineering, toxicology, or a ...

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Remote Computational Chemical Engineering information

See salary details

$92.5K

$135.2K

$161K

How much do remote computational chemical engineering jobs pay per year?

As of Jun 21, 2026, the average yearly pay for remote computational chemical engineering in the United States is $135,168.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,000.00 and $148,500.00 per year, depending on experience, location, and employer.

What is remote computational chemical engineering?

Remote computational chemical engineering is a field where engineers use computer simulations and mathematical models to design, analyze, and optimize chemical processes from a remote location. These professionals work with specialized software to predict the behavior of chemical systems, such as reaction kinetics, fluid dynamics, and material properties. By working remotely, they can collaborate with teams across the globe, contribute to research and development, and solve complex engineering problems without being physically present in a lab or office. This approach offers flexibility and access to a wider range of projects in academia, industry, and research organizations.

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

To thrive as a Remote Computational Chemical Engineer, you need a solid background in chemical engineering, advanced mathematics, and computational modeling, often supported by a relevant degree such as a BS or MS in Chemical Engineering. Proficiency with simulation software (e.g., Aspen Plus, COMSOL Multiphysics), programming languages (such as Python or MATLAB), and familiarity with cloud collaboration tools are typically required. Strong problem-solving abilities, self-motivation, and effective communication are standout soft skills for remote collaboration and project management. These skills ensure the accurate modeling and optimization of chemical processes, efficient remote teamwork, and successful delivery of complex engineering solutions.

What are some common challenges faced by remote computational chemical engineers and how can they be addressed?

Remote computational chemical engineers often encounter challenges related to effective collaboration and communication with multidisciplinary teams, as projects can involve chemists, software developers, and project managers across different time zones. Managing complex simulations and large data sets securely from a remote environment also requires robust IT infrastructure and self-discipline. To address these challenges, it's helpful to establish clear communication protocols, leverage collaboration tools, and proactively schedule regular check-ins with team members. Additionally, remote engineers should ensure they have access to reliable computing resources and seek out opportunities for virtual training to stay updated with the latest software and modeling techniques.

What is the difference between Remote Computational Chemical Engineering vs Remote Process Engineer?

AspectRemote Computational Chemical EngineeringRemote Process Engineer
Required CredentialsBachelor's/Master's in Chemical Engineering, programming skillsBachelor's/Master's in Chemical or Mechanical Engineering, process knowledge
Work EnvironmentPrimarily computer-based, data analysis, modelingDesign, optimize, and troubleshoot industrial processes remotely
Industry UsageResearch, simulation, software developmentManufacturing, refining, chemical production
Common Search/ComparisonRemote Chemical Engineering roles involving computationRemote process optimization roles

Remote Computational Chemical Engineering focuses on modeling, simulation, and data analysis using programming skills, often in research or software development contexts. In contrast, Remote Process Engineer roles involve designing and optimizing chemical processes remotely within manufacturing or production environments. Both roles require chemical engineering credentials but differ in daily tasks and industry focus.

More about Remote Computational Chemical Engineering jobs
What cities are hiring for Remote Computational Chemical Engineering jobs? Cities with the most Remote Computational Chemical Engineering job openings:
What are the most commonly searched types of Computational Chemical Engineering jobs? The most popular types of Computational Chemical Engineering jobs are:
What states have the most Remote Computational Chemical Engineering jobs? States with the most job openings for Remote Computational Chemical Engineering jobs include:
What job categories do people searching Remote Computational Chemical Engineering jobs look for? The top searched job categories for Remote Computational Chemical Engineering jobs are:
Infographic showing various Remote Computational Chemical Engineering job openings in the United States as of June 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% Remote job distribution, with an average salary of $135,168 per year, or $65 per hour.

Chemical Engineering QA Lead - Remote

YO IT Consulting

Remote

Full-time

Posted 4 days ago


Job description

Job Summary:
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking a Chemical Engineering Quality Assurance Lead to oversee quality and consistency across chemical engineering AI training projects, ensuring that engineering training data is accurate and aligned with client expectations.
Responsibilities:
• Quality monitoring: Spot-check chemical engineering items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Technical review: Evaluate AI-generated engineering explanations, process calculations, mass/energy balances, reaction engineering solutions, separation process reasoning, process-control explanations, diagrams/descriptions, and problem-solving workflows for correctness and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and chemical-engineering-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around engineering assumptions, units, formulas, balances, reaction conditions, process constraints, safety concerns, standards references, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain chemical engineering project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and chemical-engineering-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply engineering guidelines consistently and understand updates as projects evolve.
• Risk and safety review: Flag unsafe, misleading, or overconfident engineering recommendations, especially where chemicals, process conditions, reactions, plant operations, pressure systems, thermal hazards, environmental impact, or worker safety may be affected.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for chemical engineering AI training projects.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Chemical Engineering, Process Engineering, Biochemical Engineering, Materials Engineering, Petroleum Engineering, or a closely related engineering field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English.
• 3+ years of professional experience in chemical engineering, process engineering, plant operations, process design, R&D, manufacturing, process safety, technical review, engineering education, or related workflows.
• Strong understanding of core chemical engineering topics such as mass and energy balances, thermodynamics, fluid mechanics, heat transfer, mass transfer, reaction engineering, separation processes, process control, transport phenomena, and process design.
• Ability to evaluate engineering content against detailed rubrics and identify issues such as incorrect assumptions, flawed calculations, missing units, unsafe recommendations, incomplete mass/energy balances, hallucinated standards, or incomplete explanations.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation.
Preferred:
• Familiarity with common chemical engineering tools or workflows such as Aspen Plus, Aspen HYSYS, MATLAB, Python, CHEMCAD, COMSOL, process simulators, PFDs, P&IDs, Excel modeling, or process safety documentation.
• Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs.
• Experience with AI training, data annotation, large language models, prompt/response evaluation, technical content QA, or rubric-based LLM evaluation.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.