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Parallel Computing Jobs in Cambridge, MA (NOW HIRING)

Verisk

Principal Software Engineer

Boston, MA · On-site

$150K - $170K/yr

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

NorthEastern

Postdoctoral Research Associate

Boston, MA · On-site

$60K - $85K/yr

Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or large-scale data centers; Advanced experience ...

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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 13, 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
Senior Perception Software Engineer

Senior Perception Software Engineer

Pickle Robot Company

Charlestown, MA

$140K - $165K/yr

Full-time

Posted 15 days ago

Job description

About this role:

Pickle is on the hunt for a dynamic and driven Senior Perception Software Engineer to revolutionize the future of warehouse automation. This role will focus on working heavily with 3D LiDAR and other multi-sensor arrays to tackle complex challenges in state estimation, scene perception, mapping, and localization. You will play a crucial part in writing robust, production-grade software that translates raw sensor data into actionable intelligence for our robots operating in dynamic, real-world unloading docks.


What You’ll Accomplish:

  • Drive the accuracy and precision of our localization and state estimation pipelines. You will ensure reliable pose estimation of the robot's mobile base and scene components.

  • Develop advanced obstacle mapping for collision avoidance that thrives in messy environments.

  • Implement and optimize point cloud processing algorithms tailored for real-time edge compute.

  • Architect a robust software stack that efficiently parses and interfaces with the outputs of our machine learning models, integrating novel perception pipelines seamlessly into the core production codebase.

  • Improve and automate multi-sensor calibration routines. You will manage tolerance stacks and ensure high-fidelity spatial alignment across our sensor suites to guarantee a single source of truth for the robot.

Who You Are:

  • 5+ years of experience in robotics software engineering (or an MS with 3+ years of highly relevant industry experience).

  • Exceptional software engineering fundamentals, highly proficient in Python and C++ for production systems.

  • Strong mathematical foundation in linear algebra, geometry, and probabilistic robotics.

  • Hands-on experience building perception stacks using industry-standard tools and frameworks, including ROS/ROS2, OpenCV, Open3D, Eigen, and Git.

  • Hands-on experience with sensor stacks including 3D LiDARs, IMUs, and cameras.

  • You are a "full-stack" robotics engineer who cares about accuracy, precision, and edge cases in the physical world and can articulate architectural trade-offs to drive the best system level decisions.

  • Experience with optimization libraries (Ceres Solver, GTSAM), parallel computing (CUDA), Docker, and PCL preferred.

  • Willing and able to work from our HQ in Charlestown, MA, at least 3 days a week.
Pay at Pickle
At Pickle Robot Company, we believe transparency builds trust. The salary range listed here is provided in accordance with Massachusetts law and reflects what we reasonably and in good faith expect to offer for this role. We often consider candidates at different levels of seniority, and final compensation will reflect the level at which a candidate is hired, along with factors like experience and location.
 
About Pickle Robot
Want to get in on the ground floor of a fast-growing, VC-backed robotics company? Join Pickle Robot! We build systems that companies and their teams love.
 
Pickle robots unload trucks. Every day, millions of trucks and containers are loaded and unloaded, often requiring manual labor—tough, dirty, dangerous, and hard to staff. Pickle automates this process using AI, machine learning, and robotics to deliver reliable products. Our Unload Systems work with teams on loading docks to make the job safer, faster, and more efficient.
 
Pickle provides best-in-class benefits including health, dental, & vision insurance; unlimited vacation, along with all federal and state holidays; 401K contributions of 5% your salary, travel supplies, and other items to make your working life more fun, comfortable, and productive.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.