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Computer Vision Jobs in Boston

At Harnham, we understand the importance of a strong Computer Vision team who can develop bespoke algorithms and continuously innovate. We make it our mission to utilize our vast Data & Analytics knowledge to deliver a professional and quality experience.

View Computer Vision Jobs in Boston here now.

Latest Jobs

Senior Robotics Engineer - SLAM
Salary

US$130000 - US$150000 per annum

Location

Boston, Massachusetts

Description

This company is developing robotic systems that are being deployed internationally

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Senior Robotics Engineer - Defense
Salary

US$125000 - US$135000 per annum

Location

Boston, Massachusetts

Description

Join a company that has been partnering with the government for 50 years

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Head of Computer Vision
Salary

US$195000 - US$215000 per annum

Location

Boston, Massachusetts

Description

Do you have years of image processing experience in the medtech space and are looking to transition to a Director or Head Of role? this is for you!

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Lead Robotics Engineer--SLAM
Salary

US$140000 - US$155000 per annum

Location

Boston, Massachusetts

Description

Do you want to work on top tier path planning algorithms new to the market with a reputable team?

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CHIEF AI OFFICER
Salary

US$200000 - US$250000 per annum

Location

Boston, Massachusetts

Description

Lead a team influencing the insurance industry at the forefront of AI and Computer Vision

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Director of Image Processing (Hands On)
Salary

US$195000 - US$215000 per annum

Location

Boston, Massachusetts

Description

This is the perfect opportunity for a Lead Engineer to transition into a "Head Of" or "Director" level!

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Chief Computer Vision Engineer
Salary

US$250000 - US$300000 per annum

Location

Boston, Massachusetts

Description

This computer vision company is making advancements in an area that hasn't been explored by too many yet

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Senior SLAM Engineer-Path Planning
Salary

US$145000 - US$165000 per annum

Location

Boston, Massachusetts

Description

This company are creating astounding autonomous robots that can navigate the outdoors and even cut your lawn!

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Lead Computer Vision Scientist
Salary

US$150000 - US$170000 per annum

Location

Boston, Massachusetts

Description

This start up is developing technology that is changing the automotive industry

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Senior Robotics Engineer
Salary

US$120000 - US$140000 per annum

Location

Boston, Massachusetts

Description

This position is for a Senior Robotics Engineer in the Defense industry. You will be working on cutting edge technology in the robotics space.

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AI Algorithm Engineer
Salary

US$130000 - US$150000 per annum

Location

Boston, Massachusetts

Description

I am looking to speak to artificial intelligence professionals that looking for a new role in the Boston area as an AI algorithm engineer.

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Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Computer Vision in Our Day-to-Day Lives

We make micro adjustments every day to what we wear, how we shop, and how we drive. Our healthcare and industrial verticals are working with AI and Computer Vision to enhance our experiences from the user to the professional. There are a variety of computer vision applications to make life easier, more efficient, and safer. In other words, our computers have eyes. Every industry, it seems, is now touched by Computer Vision. From retail to healthcare to agriculture to banking, AI technology combines with deep learning and machine learning to help computers “see” where a car goes, an individual’s health, and what outfit might look best for any given outing. So, let’s take a look at some of the industries currently using Computer Vision. AUTOMOTIVE Human error and distractions often lead to car accidents and fatalities. According to the WHO, it’s estimated traffic accidents will be the seventh leading cause of death by 2030. To help alleviate this prediction, there is work being done on a self-driving car with sensor technology. Though autonomous cars have been tried before, this next incarnation has worked to ensure it can detect not only other cars and other large obstacles, but also pedestrians and cyclists at a distance. As it navigates through the streets autonomously, it follows traffic regulations as well as detect hand signals, and more. Efforts to train the vehicles use deep learning to predict, plan, and map its way through various scenarios. HEALTHCARE The advent of Computer Vision in technology has been a boon to the industry. It can help determine conditions of illness, reduce or eliminate misdiagnoses, and can even monitor blood loss during medical situations.  Captured images on items such as surgical sponges can be processed using Computer Vision using Machine Learning. In comparison with the human eye, the computer’s estimates were more accurate.  RETAIL  Retail has been at the forefront of many changes within the tech industry. And now, as online shopping, e-commerce, and virtual events take over traditional venues and brick-and-mortar stores, even the task of trying on clothes has gone virtual. From a virtual mirror which uses Computer Vision to help identify what outfit looks best. What may be most appropriate in what situation. Something like a movie montage, but in real time for a real person.  Retail takes things a step further by stepping up security. Using Computer Vision, retail security apps can monitor what is being recorded, what has been taken from shelves, and items being fake scanned. This information and knowledge can lead to reduced theft and other losses in stores. While other industries such as banking and agriculture have also seen a rise in Computer Vision, it’s the above which we might see in our day-to-day lives sooner rather than later. ONE FINAL THOUGHT Business processes have shifted online, looking for your next job has become more daunting than ever before. But here’s the good news. Everyone’s on the same page. Leaders, hiring managers, recruiters, and prospective employees are all navigating a new way of doing business and finding talent to keep those businesses running. In the wake of work-from-home policies, remote working, and the shifting landscape of working outside the office, technology, and particularly biotechnology careers are prime opportunities to both gain increased knowledge in your chosen field or begin your career path.  If you’re interested in Big Data & Analytics or other Data professional opportunities, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Mairead Holt

Mairead Holt

25. June 2020

Why You Should Always Be Learning In Data Science: Tips From Kevin Tran

Last month we sat down with Kevin Tran, a Senior Data Scientist at Stanford University, to chat about Data Science trends, improvements in the industry, and his top tips for success in the market.  As one of LinkedIn’s Top Voices of 2019 within Data & Analytics. his thoughts on the industry regularly garner hundreds of responses, with debates and discussions bubbling up in the comments from colleagues eager to offer their input.  This online reputation has allowed him to make a name for himself, building out his own little corner of the internet with his expertise. But for Tran, it’s never been about popularity. “It’s not about the numbers,” he says without hesitation. “I don’t care about posting things just to see the number of likes go up.” His goal is always connection, to speak with others and learn from them while teaching from his own background. He’s got plenty of stories from his own experiences. For him, sharing is a powerful way to lead others down a path he himself is still discovering.  When asked about the most important lesson he’s learned in the industry, he says it all boils down to staying open to new ideas.  “You have to continue to learn, and you have to learn how to learn. If you stop learning, you’ll become obsolete pretty soon, particularly in Data Science. These technologies are evolving every day. Syntax changes, model frameworks change, and you have to constantly keep yourself updated.”  He believes that one of the best ways to do that is through open discussion. His process is to share in order to help others. When he has a realisation, he wants to set it in front of others to pass along what he’s learned; he wants to see how others react to the same problem, if they agree or see a different angle. It’s vital to consider what you needed to know at that stage. Additionally, this exchange of ideas allows Tran to learn from how others tackle the same problems, as well as get a glimpse into other challenges he may have not yet encountered.  “When I mentor people, I’m still learning, myself,” Tran confesses. “There’s so much out there to learn, you can’t know it all. Data Science is so broad." At the end of the day, it all comes down to helping each other and bringing humanity back to the forefront. In fact, this was his biggest advice for both how to improve the industry and how to succeed in it. It’s a point he comes back to with some regularity in his writing. “It doesn’t matter how smart you are, stay humble and respect everyone,” one post reads. “Everyone can teach you something you don’t know.” Treating people well, understanding their needs, and consciously working to see them as people instead of numbers or titles—this, Tran argues, is how you succeed in the business. To learn and grow, you must work with people, especially people with different skills and mindsets. Navigating your career is not all technical, even in the world of Data. “The thing that cannot be automated is having a heart,” he tells me sagely. Beyond this, Tran stresses the need for a solid foundation. The one thing you can’t afford to do is take shortcuts. You have to learn the practicalities and how to apply them, but to be strong in theory as well.  Understanding what is happening underneath the code will keep you moving forward. He compares knowing the tools to learning math with a calculator. “If you take the calculator away, you still need to be able to do the work. You need the underlying skills too, so that when you’re in a situation without the calculator, you can still provide solutions.” By constantly striving to collaborate and improve, Tran believes the Data industry has the best chance of innovating successfully.  If you’re looking for a new challenge in an innovative and collaborative environment, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

William Reichert

William Reichert

19. March 2020

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