Register a new account with Harnham
US$155000 - US$195000 per year + BENEFITS
San Francisco, California
If you are looking for that next step in your career that will allow you to build your own team and NGS product, now is the time to make a move!
US$150000 - US$180000 per year + BENEFITS
Join a passionate biotech team in paving the way for the future of electronic health records
US$140000 - US$170000 per year + BENEFITS, UNLIMITED PTO, EQUITY
San Mateo, California
A team in the Bay Area is looking for an experienced computational biologist to come in and help develop the next revolution in imaging.
US$130 - US$160 per year + BENEFITS
Bring your passion for electronic health records to a growing start up
US$220000 - US$250000 per year + BENEFITS
Use both your expertise in biology and machine learning to change how therapeutics are developed.
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.
5 Animal Farm, Fahrenheit 451, and 1984 all wove tales of Big Brother watching. Remember when only Superman had X-ray vision and leapt tall buildings in a single bound? Well, as big tech grapples with the cause and effect of its place when it comes to facial recognition, security, and object detection, there’s a new superhero in town. Computer Vision. The Eyes Which Sweep Our World While we still can’t be everywhere or see everything at once, we have eyes everywhere. Despite security cameras, motion detectors, satellites, computers, and smartphones, there are still dangers we may miss. So, by making our machines and computers visually-enabled using Artificial Intelligence, we significantly ramp up what we can see and how fast we can process it. Still growing, Computer Vision remains in an infant stage, given that autonomous cars still can’t differentiate between a rock and paper bag or worse, a person and a static object. Despite this, there are plenty of startups on the scene working toward a solution. As Artificial Intelligence increasingly blends with Biometric technology, it lends itself more easily to image recognition, allowing computers to correctly match fingerprints and facial patterns. But, no longer is it just matching two images. Now, it’s being taught to learn the difference between static images and liveness. This could prove invaluable for: Spotting weaponsSuspicious behaviorsDangerous object detection Safety Begins at Home With products such as security cameras prevailing within the security industry, businesses are hard at work creating and improving their products using the latest technologies. One such company is working to boost the clarity of their home security cameras. Think grainy gray, blurry images from night vision options or overly bright and distorted in the day. Their camera chip will be HDR and will be able to take much clearer pictures even in low-light. At home, you might find this product in a doorbell camera which could prove quite useful for smart homes which offer the option of allowing service people into your home from a remote app on your phone. And these cameras aren’t limited to your front door: ATMsIndoor/Outdoor camerasCCTV CamerasNumber Plate Recognition Cameras Though cameras have played a role in all of these areas for some time, the idea now is to keep them from being hacked and causing damage on both a product and a personal level. And like any type of Artificial Intelligence recognition system, these camera applications are created with advanced features to protect against hacking as well super speed processing of whether or not an object is an animal, a shadow, or some kind of inclement weather. The best part? We’re only a few months away from products which can boost the benefits of many of available security cameras. The Caveat of Image Recognition Systems More and more people around the world own security cameras, not the least of which is security personnel. With this increased level of ownership, the market is expected to have over $20 billion in revenue in less than five years. With such high demand, it’s no wonder only about five percent of footage ever gets viewed. But what if security professionals could navigate up to 80 video sources on a single server? What if the algorithms, analytics, and video processing worked with cameras of all types including, but not limited to: Car dashboardsBody vestsDrone mounts With all these cameras surrounding us, the one thing to watch is that it is still humans who input the information the cameras use to process. When it comes to security professionals such as law enforcement, investigation, and government authorities its import to make sure the camera doesn’t discriminate or operate on bias. This an important issue even that even our most advanced intelligence agencies admits the algorithms for their facial recognition software are wrong about 15 percent of the time. However, one organization is working to improve and make these algorithms more ethically developed when it comes to image recognition as well as respecting individual privacy concerns. As we navigate the growing pains of new technologies, it's important to understand these solutions are meant to ensure customers, the public, and communities can trust the solutions being created. If you’re looking for a new role in Computer Vision, take a look at our latest opportunities or get in touch with one of our expert consultants: For our West Coast Team, call (415) 614 - 4999 or send an email to sanfraninfo@harnham.com. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com.
by Sam Brown
09. May 2019
It might surprise you to learn that we, humans, and machines, learn in much the same way. When we “size up a person, product, or situation” or “eyeball” a distance or measurement, our brain makes lightning quick calculations and guesses. From this, we’re able to reason and making relational assessments of separate items bound together by their similarities. These tasks, we accomplish as early as about 18-months old. This is what we’re working on getting computers to do as well, though we’re not quite there, yet. And just as children learn block by block and bit by bit, so too can we teach AI. Computer Vision, when it comes to the industry of robotics, offers one of the most challenging aspects of the latest technological advancements. Keeping Up Appearances Humans take in, process, acknowledge, and understand information in order to act, but the replication of this human software has been challenging. One way in which companies are meeting this challenge is combine Computer Vision hardware with software algorithms and Deep Learning to help teach computers to better “see” objects and identify them accurately. But like the inner-workings of the human mind, Machine Vision and Deep Learning touch on several areas such as actual and predicted Computer Vision reporting, the three-pronged recipe of a Computer Vision system, and a product development ecosystem which gets to the root of the technology. According to one report, Computer Vision in robotics is expected to grow significantly over a 7-year period. Some of the markets expected to see growth and making major investments include semiconductor manufacturers, software companies, and product developers. The Building Blocks The Deep Learning Engineer is to Computer Vision what the Data Engineer is to Data Science. In both regards, these professionals must begin with a solid foundation and build from there. In order to achieve 100% accuracy, hardware and software improvements must get underway and are tantamount to a fully developed ecosystem of Computer Vision product development. Acceleration of this rapidly evolving industry is due to a number of factors: Wide availability of wireless networks to millions of people worldwide.Deep Learning advances.More cost-effective chipsets.Images that can be processed, analyzed, and transmitted more easily with availability of high bandwidth.Open source libraries help to build differentiated products without reinventing the wheel every time when it comes to infrastructure. On the flipside, there are some barriers to overcome as well. These include, but are not limited to: Cost issues due to the fact that most advances take place in university research labs or big companies.A skills shortage of hardware engineers with Computer Vision and Deep Learning experience.A lack of recognized applications for these products, though the closest attempt may be self-driving cars. Though these considerations may seem unsurmountable in the short-term, they do provide plenty of opportunity for those in design automation. From the initial analysis to servers in the cloud, and high-level solutions to help computers make informed decisions. Looking Ahead So, what happens when we teach computers to think as we do? Will there be a battle for domination of one species over another? Probably not. But one of the biggest challenges to get to the next level in automated machine learning is understanding how much our thinking process involves predictions. This is important in fields which must coordinate information based on exterior data. This type of learning has impacted a variety of fields from online shopping to medical diagnosis. The massive amount of data available for consumption is staggering. Not only are Deep Learning and Machine Learning products of corporate and scientific solutions, they are also being put in the palm of our hand; our homes, our cars, and our handheld devices in order to help us more efficiently complete jobs which might be too slow going or for which mistakes are prone. If you’re interested in industrial robotics and the AI space, we may have a role for you. We specialize in junior and senior roles and have numerous opportunities in Computer Vision. Take a look at our current vacancies or get in touch with one of our expert consultants: For our West Coast Team, call (415) 614 - 4999 or send an email to sanfraninfo@harnham.com. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com.
02. May 2019
Read about Harnham's corporate social responsibility initiatives
Find our more about the causes we support.
