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Remote Computational Chemical Engineering Jobs (NOW HIRING)

Morson Talent

Chemistry Systems Engineer

$65 - $85/hr

Remote, candidates must reside in USA. Duration: 18 Months Vacancies: 2 Hourly Rate: $65.00- $85.00 ... Qualifications S. degree in Chemistry, Chemical Engineering or other similar discipline from an ...

micro1 AI

Cheminformatics Specialist - Remote

Pueblo, CO · Remote

$80 - $110/hr

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank ...

micro1 AI

Cheminformatics Specialist - Remote

Aurora, CO · Remote

$80 - $110/hr

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank ...

micro1 AI

Cheminformatics Specialist - Remote

Tucson, AZ · Remote

$80 - $110/hr

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank ...

micro1 AI

Cheminformatics Specialist - Remote

Austin, TX · Remote

$80 - $110/hr

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank ...

micro1 AI

Cheminformatics Specialist - Remote

Conroe, TX · Remote

$80 - $110/hr

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank ...

micro1 AI

Cheminformatics Specialist - Remote

Spokane, WA · Remote

$80 - $110/hr

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank ...

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Remote Computational Chemical Engineering information

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$92.5K

$135.2K

$161K

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

As of Aug 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?

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:

Remote Computational Chemical Engineering jobs near you
Infographic showing various Remote Computational Chemical Engineering job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 4% Part Time, 3% Contract, and 1% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $135,168 per year, or $65 per hour.

Computational Biology MLOps Engineer (Remote)

Marlabs

San Diego, CA • Remote

$114K - $134K/yr

Full-time

Posted 9 days ago

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Computational Biology MLOps Engineer to join our innovative and dynamic team.

This role requires onsite work three (3) days per week in Indianapolis, IN or San Diego, CA.

Computational Biology MLOps Engineer | About You

As a Computational Biology MLOps Engineer, you are responsible for building and scaling the ML infrastructure that supports next generation in silico protein design and engineering. You bridge cutting edge AI research and production systems at the intersection of machine learning, computational biology, and high performance computing. You thrive in cross functional environments and partner closely with computational scientists and platform engineers to accelerate research velocity. You bring strong software, DevOps, and data engineering fundamentals with hands on experience across CI/CD, orchestration, and distributed training. Experience working with scientific or multimodal data and interest in protein language and generative models is a plus.

Computational Biology MLOps Engineer | Day-to-Day

  • Build and maintain ML infrastructure, including CI/CD pipelines (GitHub Actions) for model training, evaluation, and deployment.
  • Orchestrate compute across Kubernetes clusters and SLURM and HPC environments to optimize utilization for large scale training.
  • Develop robust and scalable data pipelines that deliver ML ready datasets from biological sources such as PDB and mmCIF files, sequence databases, and assay readouts.
  • Create tools and frameworks that enable rapid iteration on protein language models, diffusion models, and other generative approaches.
  • Architect systems that scale across distributed environments and support multimodal datasets for large foundational models.
  • Implement monitoring, logging, and alerting to ensure reliability, performance, and cost efficiency of production ML systems.

Computational Biology MLOps Engineer | Skills & Experience

  • 5+ years of overall industry experience in software engineering, DevOps, data engineering, or ML engineering roles, including 3+ years of focused MLOps experience building and maintaining production grade ML infrastructure.
  • Proven CI/CD expertise with GitHub Actions and strong DevOps practices including infrastructure as code, version control, and collaborative workflows.
  • Hands on Kubernetes experience in deploying and managing containerized ML workloads with familiarity using container registries.
  • Proficiency with SLURM or similar job schedulers in HPC environments and experience with distributed training optimization including mixed precision and checkpointing.
  • Strong Python skills and experience with major ML frameworks including PyTorch, TensorFlow, or JAX.
  • Experience building ETL processes and scalable data and feature pipelines and experience with cloud platforms such as AWS, GCP, or Azure.
  • Preferred experience with scientific data, protein structure formats such as PDB and mmCIF, protein AI models including ESM, and agentic systems such as MCP, LangGraph, and LangChain.