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Parallel Computing Jobs in Cambridge, MA (NOW HIRING)

Nvidia

Senior GPU Architect

Westford, MA

$134K - $182K/yr

A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly ...

Nvidia

Senior Developer Technology Engineer - AI

Westford, MA · Hybrid

$56.75 - $74.75/hr

Are you a creative and autonomous computer scientist with a genuine passion for parallel computing? If so, we want to hear from you. Come, join our AI Compute DevTech team and help build the real ...

The Hollister Group

Full Stack Engineer

Boston, MA · On-site

... parallel computing, and experience with both relational and non-relational databases. • Experience optimizing software systems for performance, scalability, and cloud deployment. • Ability to ...

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All JobsParallel Computing JobsParallel Computing Jobs in Cambridge, MA

Parallel Computing information

See Cambridge, MA salary details

$27.3K

$57.2K

$98.9K

How much do parallel computing jobs pay per year?

As of Jun 21, 2026, the average yearly pay for parallel computing in Cambridge, MA is $57,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,700.00 and $65,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Parallel Computing Specialist, you need strong knowledge of computer architecture, parallel algorithms, and experience with programming languages such as C/C++, Python, and frameworks like MPI or OpenMP, often supported by a degree in computer science or a related field. Familiarity with high-performance computing (HPC) environments, GPU programming (CUDA, OpenCL), and cloud-based parallel processing systems is typically required. Analytical thinking, problem-solving abilities, and effective collaboration are crucial soft skills in this role. These skills are vital for efficiently designing, optimizing, and implementing solutions that leverage parallelism to significantly accelerate computational tasks.

What are some common challenges faced by professionals working in parallel computing roles?

Professionals in parallel computing often encounter challenges such as efficiently dividing complex tasks among multiple processors and minimizing communication overhead between them. Debugging and optimizing performance across parallel architectures can be difficult, as issues like race conditions and load imbalances frequently arise. Additionally, staying current with evolving hardware technologies and parallel programming frameworks is essential to ensure solutions remain efficient and scalable. Collaborating with cross-functional teams, such as data scientists and system architects, is also crucial for integrating parallel solutions into larger projects.

What is the difference between Parallel Computing vs Data Analyst?

AspectParallel ComputingData Analyst
Required CredentialsComputer Science or Engineering degree, programming skillsStatistics, Data Science, or related degree, analytical skills
Work EnvironmentResearch labs, tech companies, high-performance computing centersBusiness, finance, healthcare, corporate offices
Industry UsageTechnology, research, scientific computingBusiness intelligence, market analysis, reporting

While Parallel Computing focuses on developing algorithms to process large data sets efficiently across multiple processors, Data Analysts interpret data to provide actionable insights. Both roles require strong technical skills but serve different purposes: one enhances computational performance, the other informs business decisions.

What is parallel computing?

Parallel computing is a type of computation where many calculations or processes are carried out simultaneously, leveraging multiple processors or computers to solve complex problems more efficiently. It divides large tasks into smaller ones that can be executed concurrently, significantly speeding up processing time. Commonly used in scientific research, data analysis, and engineering, parallel computing is essential for handling large-scale simulations and big data applications.
What are popular job titles related to Parallel Computing jobs in Cambridge, MA? For Parallel Computing jobs in Cambridge, MA, the most frequently searched job titles are:
What job categories do people searching Parallel Computing jobs in Cambridge, MA look for? The top searched job categories for Parallel Computing jobs in Cambridge, MA are:
Parallel Computing jobs near you
Infographic showing various Parallel Computing job openings in Cambridge, MA as of June 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 74% Physical, 6% Hybrid, and 20% Remote job distribution, with an average salary of $57,228 per year, or $27.5 per hour.
High Performance Computing Engineer

High Performance Computing Engineer

Watershed Informatics

Boston, MA • On-site

Other

Posted 24 days ago

Job description

About Watershed

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis - from lab data to plot - with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that's intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives - all while bringing transformational change to a $40 billion industry.

Responsibilities
  • Integrate software libraries and cluster computing frameworks into high performance applications
  • Develop solutions for benchmarking, metric collection, and monitoring of resources
  • Collaborate with software engineers to optimizing software and maximize computational throughput
Qualifications
  • Experience in all of the following areas: parallel computing, distributed computing, computer architecture, and software optimization
  • Programming experience in Python, C/C++, and Bash
  • Experience working with Unix/Linux, containerization, and cloud environments
  • Familiarity with networking, security, and the Linux operating system
  • Ability to analyze very complex problems and come up with novel solutions

Watershed is an equal-opportunity employer and believes diversity of all types is integral to company success. We do not discriminate on the basis of religion, sexual orientation, gender identity, race, ethnicity, national origin, marital status, veteran status, or disability status.

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