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Computer Science Environmental Jobs in Boston, MA

Atlas

EIR Environmental Scientist I

Woburn, MA · On-site

$25 - $28/hr

The Environmental Scientist I will be Responsible for performing field data collection and sampling ... Proficient in MS Word, Excel, PowerPoint, and other widely used computer programs * Possess ...

Cybercoders

AI/ML Engineer - Computer Vision

Cambridge, MA · On-site +1

$121K - $143K/yr

Bachelor's degree in Computer Science, Engineering, Machine Learning, or a related field Preferred ... Experience deploying machine learning models into production environments * Experience with edge ...

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All JobsComputer Science Environmental JobsComputer Science Environmental Jobs in Boston, MA

Computer Science Environmental information

See Boston, MA salary details

$44.5K

$91.4K

$133.6K

How much do computer science environmental jobs pay per year?

As of Jun 21, 2026, the average yearly pay for computer science environmental in Boston, MA is $91,392.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,500.00 and $107,000.00 per year, depending on experience, location, and employer.

What kinds of projects do Computer Science Environmental professionals typically work on?

Professionals in Computer Science Environmental roles commonly work on projects such as developing models to predict the impacts of climate change, creating software tools for environmental data analysis, or building systems for monitoring air and water quality. You may collaborate with environmental scientists, engineers, and policy makers to design technology-based solutions that address environmental issues. These projects often involve handling large data sets, implementing algorithms, and visualizing results for diverse audiences. This dynamic role offers the opportunity to make a tangible impact on sustainability efforts by leveraging your technical expertise in real-world applications.

How is computer science related to environmental science?

Computer science environmental roles involve developing algorithms, data analysis, and modeling tools to monitor and address environmental issues such as climate change, pollution, and resource management. Skills in programming, data visualization, and environmental data analysis are essential for these positions.

What are the key skills and qualifications needed to thrive in the Computer Science Environmental position, and why are they important?

To thrive as a Computer Science Environmental professional, you should possess a solid background in computer science, data analysis, and environmental science, often supported by a relevant degree. Familiarity with programming languages (such as Python or R), geographic information systems (GIS), climate modeling software, and environmental databases is typically required. Strong problem-solving skills, attention to detail, and collaborative communication help individuals stand out in multidisciplinary teams. These skills are vital for effectively developing, analyzing, and implementing technology-driven solutions to complex environmental challenges.

What is the highest paying job in environmental science?

In environmental science, environmental managers and directors typically have the highest salaries, often earning over $100,000 annually. These roles require strong leadership, project management skills, and often advanced degrees or certifications in environmental policy or management.

Is computer science dead due to AI?

Computer science remains a vital field for roles such as software developers, data scientists, and AI specialists. AI advances create new opportunities for innovation, requiring skills in programming, algorithms, and machine learning tools, ensuring ongoing demand for computer science expertise.

What is a Computer Science Environmental job?

A Computer Science Environmental job involves applying computer science skills to solve environmental challenges, such as climate modeling, data analysis for sustainability, or developing software for environmental monitoring. Professionals in this field work with big data, machine learning, and simulation models to assess environmental impacts and optimize resource management. They may collaborate with scientists, policymakers, and engineers to develop technology-driven solutions for conservation, pollution control, and energy efficiency.

What are 5 careers in environmental science?

Environmental science offers careers such as environmental scientist, conservation scientist, environmental engineer, wildlife biologist, and environmental policy analyst. These roles often require knowledge of ecology, data analysis, and environmental regulations, and may involve fieldwork, research, or policy development.
What are the most commonly searched types of Computer Science Environmental jobs in Boston, MA? The most popular types of Computer Science Environmental jobs in Boston, MA are:
What are popular job titles related to Computer Science Environmental jobs in Boston, MA? For Computer Science Environmental jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Computer Science Environmental jobs in Boston, MA look for? The top searched job categories for Computer Science Environmental jobs in Boston, MA are:
Computer Science Environmental jobs near you
Infographic showing various Computer Science Environmental job openings in Boston, MA as of June 2026, with employment types broken down into 76% Full Time, 18% Part Time, 2% Temporary, 2% Contract, and 2% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $91,392 per year, or $43.9 per hour.

Research Scientist, Dexterous Manipulation & Robot Learning

Lila Sciences

Cambridge, MA

Other

Posted 29 days ago

Job description

Your Impact at LILA

As a Robotics Scientist at Lila, you will lead the research and development of autonomous robotic systems that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You'll develop novel algorithms and deploy intelligent robotic solutions that interact seamlessly with human scientists and complex lab environments. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.

What You'll Be Building

  • Pioneering approaches for precise and dexterous robotic manipulation that leverage foundation models, reinforcement learning, diffusion-based methods, and human guidance to enable adaptive and intelligent robotic systems capable of complex tasks across diverse scientific environments
  • Developing novel human-robot interaction frameworks that incorporate imitation learning, and learning from human guidance, feedback, demonstrations and corrections, creating intelligent robotic agents that can seamlessly integrate with human scientific workflows and rapidly adapt to new experimental contexts
  • Advancing dexterous manipulation research through cutting-edge machine learning approaches, including diffusion models and adaptive learning algorithms, that synthesize multi-modal sensing (tactile, visual, and language) to develop generative skill representation sand sophisticated motor learning policies for intelligent robotic systems
  • Designing autonomous robotic systems with trust calibration mechanisms, enabling intelligent agents that can dynamically adjust their behaviors based on contextual information in complex scientific tasks

What You'll Need to Succeed

  • Ph.D. in Robotics, Machine Learning, Computer Science, or a related field with demonstrated expertise in foundation models for robotic learning
  • Advanced proficiency in reinforcement learning, diffusion-based methods, imitation learning, and adaptive learning algorithms for robotic manipulation
  • Expert-level experience with machine learning frameworks (PyTorch, TensorFlow) and deep learning architectures for developing foundation models, with specific expertise in diffusion-based generative models for robotics
  • Proven track record of developing multi-modal perception systems integrating tactile, visual, language and other contextual sensing for intelligent robotic agents
  • Strong publication record in robot learning, demonstrating innovative approaches to trust calibration, contextual learning, and generative robotic skill learning

Bonus Points For

  • Research contributions to foundation models and diffusion methods in robotics
  • Experience with large-scale machine learning model development, particularly generative and diffusion-based approaches
  • Expertise in human-in-the-loop learning, correction-based training paradigms, and diffusion-guided skill transfer
  • Demonstrated ability to translate theoretical machine learning research, especially diffusion and generative models, into practical robotic implementations

Apply