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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 ...

Verisk

Principal Software Engineer

Boston, MA · On-site

$146K - $196K/yr

Preferred : • AWS platform development. • C#, Angular, Python, SQL • PostGres, Glue, Aurora • Background in algorithms, high-performance distributed and parallel computing • Knowledge of ...

The Hollister Group

UI Engineer (React/Python)

Boston, MA · On-site

$113K - $151K/yr

Strong backend engineering skills using Python, Ray, FastAPI, and Pandas/Polars, including API design, distributed parallel computing, and experience with both relational and non-relational databases.

Aquila Technology

Field Technician

Lexington, MA

$22 - $30.25/hr

The Field Technician will work with an interactive, on-demand parallel computing system that uses large computing clusters to enable researchers to augment the power of desktop systems to process ...

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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 Jul 11, 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.

Is parallel computing difficult?

Parallel computing as a job involves designing and implementing systems that perform multiple tasks simultaneously, which requires strong problem-solving skills, knowledge of algorithms, and proficiency with programming tools like MPI or OpenMP. The difficulty depends on the complexity of projects and the individual's experience, but mastering parallel algorithms and debugging concurrent processes can be challenging for beginners. Continuous learning and practical experience are essential for success in this field.

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 is the highest paying job in computing?

In computing, roles such as Chief Technology Officer (CTO), Solutions Architect, and Data Science Director tend to be among the highest paying, often earning six-figure salaries. Specialized skills in areas like artificial intelligence, cybersecurity, and cloud computing can also command top compensation levels for experienced professionals.

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 engineers make $500,000?

Senior engineers in fields such as software, aerospace, or petroleum engineering can earn $500,000 or more annually, often through a combination of base salary, bonuses, and stock options. High compensation typically requires extensive experience, advanced skills, and working in high-demand industries or leadership roles.

What is an example of parallel computing in real life?

Parallel computing in a job context involves tasks like processing large datasets or simulations simultaneously across multiple processors or cores to improve efficiency. For example, data analysts may use parallel computing tools to analyze big data sets quickly, requiring knowledge of programming languages such as Python or C++ and familiarity with parallel processing frameworks like MPI or OpenMP.
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
High Performance Computing Engineer

High Performance Computing Engineer

Watershed Informatics

Boston, MA

Other

Posted 14 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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