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Perception Jobs in Boston, MA (NOW HIRING)

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Perception information

See Boston, MA salary details

$32.1K

$169.4K

$255.9K

How much do perception jobs pay per year?

As of Aug 18, 2026, the average yearly pay for perception in Boston, MA is $169,376.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,024.00 and $198,042.00 per year, depending on experience, location, and employer.

What is a perception job?

A Perception job typically involves developing and improving a system's ability to interpret and understand sensory data, often in fields like robotics, autonomous vehicles, and computer vision. Professionals in this role work with sensor fusion, machine learning, and computer vision algorithms to detect, track, and classify objects in an environment. Their goal is to enable machines to perceive and react to their surroundings accurately, enhancing safety and efficiency.

What are the key skills and qualifications needed to thrive as a perception engineer, and why are they important?

To thrive as a Perception Engineer, you need strong foundations in computer vision, robotics, and sensor fusion, typically supported by a degree in computer science, robotics, or a related field. Familiarity with tools like ROS, OpenCV, TensorFlow, and experience working with LiDAR, radar, or camera systems are highly valuable. Excellent problem-solving skills, adaptability, and effective communication help you collaborate within multidisciplinary teams and tackle complex technical challenges. These skills are crucial for developing reliable perception systems that enable autonomous machines to interpret and interact safely with real-world environments.

What are some common challenges faced by professionals working in perception roles within autonomous vehicle development teams?

Professionals in perception roles often encounter challenges related to processing large volumes of sensor data, such as lidar, radar, and cameras, in real time to ensure accurate object detection and scene understanding. Balancing the need for high accuracy with the computational limitations of embedded systems can be demanding. Additionally, perception engineers frequently collaborate with teams in sensor fusion, mapping, and planning, requiring strong communication and interdisciplinary problem-solving skills. Adapting to rapidly evolving technologies and continuously improving algorithms to handle edge cases in complex environments are also key aspects of the role.

What is the difference between Perception vs Data Analyst?

AspectPerceptionData Analyst
Required CredentialsVaries; often no formal certification requiredBachelor's degree in statistics, data science, or related field; certifications like CAP or Microsoft Data Analyst
Work EnvironmentResearch, consulting, or strategic planning settingsBusiness, finance, healthcare, and tech industries
Employer & Industry UsageUsed in marketing, psychology, and strategic rolesCommon in corporate, finance, and tech sectors
Search & Comparison IntentUnderstanding how perceptions influence decisionsAnalyzing data to inform business strategies

Perception focuses on how individuals interpret and understand information, often in psychological or strategic contexts. Data Analysts interpret and analyze data sets to support business decisions. While perception is more subjective and qualitative, Data Analysts rely on quantitative data analysis. Both roles are essential in decision-making processes but serve different functions within organizations.

What are the most commonly searched types of Perception jobs in Boston, MA?

The most popular types of Perception jobs in Boston, MA are:

What job categories do people searching Perception jobs in Boston, MA look for?

The top searched job categories for Perception jobs in Boston, MA are:

Perception jobs near you
Infographic showing various Perception job openings in Boston, MA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $169,376 per year, or $81.4 per hour.

Senior Staff Software Engineer, Perception (R4985)

Shield AI

Boston, MA • On-site

$233K - $350K/yr

Full-time

Posted 20 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities.
 
In this role, you'll develop and deploy advanced machine learning models that enable autonomous systems to better understand, reason about, and interact with their environment. You'll partner closely with machine learning researchers, autonomy engineers, perception engineers, and platform teams to translate emerging AI capabilities into reliable, production-ready systems for U.S. and international defense customers. This is an ideal opportunity for engineers who enjoy building state-of-the-art AI systems while solving the practical challenges of deploying them on operational autonomous platforms. 
What You'll Do:

Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. 

Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. 

Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. 

Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. 

Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. 

Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. 

Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. 

Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. 

Required Qualifications:

  • Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.

  • Mastery of machine learning fundamentals. 

  • Experience training an deploying ML models for computer vision in a production setting. 

  • Strong understanding of 3D vision problems/algorithms. 

  • Experience with machine learning frameworks such as PyTorch and TensorFlow. 

  • Demonstrated expertise in deploying models using TensorRT and ONNX. 

  • Proficiency in C++ and Python. 

  • Strong analytical and problem-solving skills, with the ability to translate research into practical applications. 

  • Ability to obtain a SECRET clearance 
Preferred Qualifications:

  • Experience with developing autonomous systems for defense customers. 

  • Experience with training/finetuning vision-language models, vision-language-action models, and/or world models.  

  • Contributions to open-source projects in machine learning or computer vision. 

  • Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).

#LI-DS-1
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Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

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.