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Computer Engineering Jobs in Amherst, MA (NOW HIRING)

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Computer Engineering information

See Amherst, MA salary details

$47.8K

$119.7K

$135.4K

How much do computer engineering jobs pay per year?

As of Sep 11, 2026, the average yearly pay for computer engineering in Amherst, MA is $119,676.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,800.00 and $129,500.00 per year, depending on experience, location, and employer.

What is computer engineering?

Computer engineering is a field that combines principles of electrical engineering and computer science to design, develop, and maintain computer systems and hardware. Computer engineers work on both the hardware (such as processors, circuit boards, and memory devices) and the software that runs on these systems. Their work enables the creation of everything from smartphones and laptops to complex embedded systems in cars and medical devices. Computer engineering can also involve research, innovation, and improving the efficiency and performance of computers and related technologies.

What are the key skills and qualifications needed to thrive as a computer engineer?

To thrive as a Computer Engineer, you need strong analytical skills, proficiency in computer architecture, hardware and software design, and at least a bachelor's degree in computer engineering or a related field. Familiarity with programming languages (such as C/C++ or Python), hardware description languages (like VHDL or Verilog), and tools like MATLAB or CAD software is common, and certifications like Cisco or CompTIA can be beneficial. Problem-solving abilities, teamwork, and effective communication are vital soft skills for collaborating on complex projects and troubleshooting technical issues. These skills and qualifications are essential for designing innovative computing solutions, ensuring reliable system performance, and succeeding in multidisciplinary engineering environments.

How do computer engineers typically collaborate with other departments in a tech company?

Computer engineers often work closely with software developers, hardware designers, and product managers to bring complex systems to life. Collaboration usually involves regular meetings to align on project goals, troubleshooting cross-disciplinary issues, and integrating hardware and software components. Effective communication and teamwork are essential, as computer engineers must translate technical requirements and constraints between teams to ensure a smooth development process. This collaborative environment helps broaden your skill set and exposes you to various aspects of product development.

What is the difference between Computer Engineering vs Computer Science?

AspectComputer EngineeringComputer Science
Required CredentialsBachelor's in Computer Engineering or related fieldBachelor's in Computer Science or related field
Work EnvironmentHardware and software development, embedded systems, device designSoftware development, algorithms, data structures, theoretical computing
Employer & Industry UsageTech companies, hardware firms, embedded systems companiesSoftware firms, research institutions, tech startups
Common Search & ComparisonYesYes

Computer Engineering focuses on designing and developing hardware and embedded systems, combining electrical engineering and computer science principles. Computer Science emphasizes software development, algorithms, and theoretical aspects of computing. While both fields overlap, Computer Engineering leans more toward hardware integration, whereas Computer Science centers on software and programming.

What do I do with a computer engineering degree?

A computer engineering degree prepares individuals for roles such as hardware engineer, software developer, systems analyst, or network administrator. Graduates often work in technology companies, design embedded systems, develop software, or manage computer networks, utilizing skills in programming, circuit design, and systems integration.

What is the job of a computer engineer?

A computer engineer designs, develops, and tests computer hardware and software systems. They work with programming languages, circuit design, and system integration to create efficient computing solutions, often collaborating with software developers and IT professionals.

What are the most commonly searched types of Computer Engineering jobs in Amherst, MA?

The most popular types of Computer Engineering jobs in Amherst, MA are:

What cities near Amherst, MA are hiring for Computer Engineering jobs?

Cities near Amherst, MA with the most Computer Engineering job openings:

Computer Engineering jobs near you
Infographic showing various Computer Engineering job openings in Amherst, MA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, 2% Contract, and 1% Nights. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution, with an average salary of $119,676 per year, or $57.5 per hour.

Computer Vision & AI/ML Engineer Jobs

Springfield, MA • On-site

AIToolboard
See more jobs at AIToolboardexternal

$111K - $133K/yr

Other

Re-posted 6 days ago

Job description

Aqua IT Springfield, US

Full-time

About the Role

Description of Services/Responsibilities:

  • Design and execute fine-tuning pipelines for Vision-Language Models (VLMs) on domain-specific imagery datasets, including data preprocessing, training orchestration, and hyperparameter optimization
  • Develop and implement evaluation frameworks for multimodal model performance, including task-specific metrics for image understanding, visual question answering, and spatial reasoning
  • Build scalable training infrastructure on AWS (SageMaker, EC2 GPU instances) for distributed fine-tuning of large multimodal models
  • Engineer data pipelines for curating, annotating, and transforming geospatial imagery datasets into model-ready formats for supervised and instruction-tuning workflows
  • Collaborate with applied scientists and solutions architects to iterate on model architectures, adapter strategies (LoRA/QLoRA), and inference optimization techniques
Basic Requirements
  • TS/SCI with CI Poly required with current NGA eligibility and SBU/SECNet/COE accounts
  • Must be willing to work in SCIF daily or as needed
  • 5+ years of professional machine learning engineering experience with a focus on deep learning
  • 1+ years of hands-on experience fine-tuning large foundation models (LLMs or VLMs)
  • Experience with parameter-efficient fine-tuning methods (LoRA, QLoRA, adapters)
  • Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques
  • 4+ years of advanced Python development for ML workloads
  • Strong proficiency with PyTorch and the HuggingFace ecosystem (Transformers, PEFT, Datasets, Accelerate)
  • Experience with distributed training frameworks (DeepSpeed, FSDP, or Megatron)
  • 3+ years of experience with computer vision or multimodal models
  • Understanding of vision transformer architectures (ViT, CLIP, LLaVA-family models, or similar)
  • Experience processing and augmenting image datasets at scale
  • 3+ years of experience with AWS ML infrastructureSageMaker Training jobs, Processing jobs, and endpoint deploymentGPU instance selection, multi-node training, and cost optimization on EC2 (P4/P5/G5/G6e)S3 data management for large-scale training datasets
  • 2+ years of experience building ML evaluation pipelinesAutomated benchmarking, metric computation, and result analysisExperience with both quantitative metrics and qualitative/human evaluation approaches
  • Strong software engineering fundamentals (version control, testing, CI/CD for ML workflows)
Preferred Qualifications
  • 2+ years of experience with geospatial or remote sensing imagery
  • Familiarity with electro-optical and SAR satellite imagery formats and characteristics
  • Understanding of geospatial metadata, coordinate systems, and imagery preprocessing
  • Experience with model quantization and inference optimization (vLLM, TensorRT, ONNX)
  • Experience with MLOps and experiment tracking tools (MLflow, Weights & Biases, SageMaker Experiments)
  • Familiarity with data annotation platforms and active learning workflows for imagery
  • Experience with containerized ML workflows (Docker, ECR, ECS/EKS)
  • 2+ years of experience with Authority to Operate (ATO) processes in government environments
  • Implementation of NIST 800-53 controls and security compliance for ML systems
  • Experience deploying models in air-gapped or disconnected environments
  • Familiarity with multimodal evaluation benchmarks (MMMU, MMBench, GQA, or domain-specific equivalents)
  • Publications or demonstrated contributions in computer vision, VLMs, or multimodal AI
  • Experience with synthetic data generation for training data augmentation

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