Computer Vision Engineer

Boston, Massachusetts
US$150000 - US$200000 per year

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Computer Vision Engineer - SLAM

Boston, MA
$200,000 + Equity, Bonus

Harnham have been retained by a global leader in robotics, with offices across multiple locations. They are building a new R&D center in the heart of the Boston technology scene, and are looking to bring on multiple computer vision engineers within object detection and collision avoidance. The role is reporting directly into the Head of the lab, and you be responsible for spearheading all autonomy programs for the group.

The role

  • Building detection algorithms in C++, Python and Matlab
  • Utilizing deep learning technologies, such as TensorFlow, Caffe and PyTorch
  • Building algorithms for robotic collision avoidance
  • Working closely with the R&D Lead, as well as cross functional mechanical engineering teams
  • Conducting leading research into deep learning, robotics and computer vision

Experience Required

  • 3+ years in real world industry building computer vision algorithms in C++
  • Experience in researching deep learning, and working with tools such as TensorFlow, Caffe and PyTorch
  • Experience in object detection and collision avoidance
  • A combination of hands on software engendering with research
  • PhD/Master's Degree - Computer Science or related
  • Must be US citizen or Greencard holder
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SB-CV122
Boston, Massachusetts
US$150000 - US$200000 per year

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Machine Learning: How AI Learns

Machine Learning: How AI Learns

Amazon has begun curating summer reading lists. How? Patterns. Facebook shows you ads for items you may have been searching for online. How? It learns from your browsing habits. Ever wondered how Facebook knows you were just looking at that pair of shoes or that particular guitar. The Data you feed it, feeds its brain. In other words, this is how Artificial Intelligence learns. Machine Learning. Whilst it can be disconcerting to know that a machine understands our buying habits, that’s not the only thing it’s used for. It’s also a pivotal tool in such areas as Bionformatics, Biostatistics, Computational Biology, Robotics, and more.  What is Machine Learning? Ultimately, it’s a method of Data Analysis which helps to automate model building and is part of Artificial Intelligence. In other words, it helps to solve Computational Biology problems by learning from Data to identify patterns and make decisions with little human intervention. This helps scientific researchers learn about many aspects of biology. However, running a Machine Learning project can be difficult for beginners, who may experience issues when trying to navigate the information without making mistakes or second guessing themselves. This is one of the reasons a Computational Biologist might want to upskill with a course or two in Machine Learning for a more robust understanding of the information being learned and applied.  The Good News and the Bad With each shift of industrial revolution, there has been one system which has made an indelible mark on our daily lives and the Fourth Industrial Revolution is no different. Just like we can no longer imagine factories without assembly lines, we can also no longer imagine not having Siri, Google Maps, or online recommendations. But, as exciting and as important as these things are, Machine Learning has become so crucial to our daily lives, so complex, it takes a technology expert to master it leaving it nearly inaccessible to those who could benefit from it. Why is Machine Learning Important? By building models to peel back the layers and discover connections, organisations can more easily and more quickly make improved decisions with little to no human intervention. Computational processing is both more affordable and more powerful. It’s possible to quickly scale and produce models which can analyse bigger and more complex data and there’s also a chance to identify opportunities and to help avoid any unknowns such as risk. Machine Learning is used in every industry from Retail to Financial Services to Healthcare. Here are just a few ways it has already transformed our world. Retail – Retailers are able to learn from their customers buying habits, predictive buying habits, how to personalise a shopping experience, price optimisation, and customer insights.Financial services – Machine Learning helps to prevent fraud and identify Data insights.Healthcare – Wearable devices allow for real-time data to assess a patient’s health. Medical professionals can also more quickly find red flags which can help improve diagnoses and treatment.Oil and gas – It cannot only help find where oil might be, but also predict refinery sensory failure, and streamline distribution.Transportation – Help to make routes more efficient and predict problems that could affect the bottom line. While humans can create at least one or two models a week; Machine Learning can create thousands.  Ultimately, the goal of Machine Learning is to understand the structure of Data. As it learns to determine what Data is needed for its structure, it can be easily automated and sift through Data until a pattern is found. This is how machines learn. If you’re looking to take your next step in the field of Machine Learning, we may have a role for you. Take a look at our latest opportunities, or get in touch to see if we can help you take that next step.

Five Strategies To Modernise Your Workplace And Create A Smart Office

Five Strategies To Modernise Your Workplace And Create A Smart Office

By Laura Gayle, BusinessWomanGuide.org Smart technology is rapidly reshaping society. From cloud storage and mobile access to the internet of things and artificial intelligence, what was once regarded as science fiction is steadily becoming reality. In response, many employers are finding ways to modernize their workplaces by creating smart offices — not because it looks cool or is the trendy thing to do, but because they've discovered that doing so provides several tangible benefits. New devices, apps, and AI-driven tools can not only make your office smarter, they also can position you for better marketing and sales efforts and provide competitive advantages in your industry. Additionally, creating a smart office offers both employees and customers a seamless experience and can attract talented millennial workers. Since millennials naturally adapt to tech innovations, they can assist in this transition to bring your company to the next level. Here are five strategies to modernise your workplace with smart tech. 1. Use cloud-based storage Cloud-based storage offers both convenience and efficiency. Many among today's workforce probably don't even realise there was a time when offices were full of filing cabinets and computer equipment. Now that mobile access has been fully integrated into nearly all workplaces, much of the bulky equipment that previously took up space is disappearing. Filing cabinets? Paper files? Things of the past. Workers today don't typically spend hours every week filing stacks of papers because most documents are digitised and stored in the cloud. Other cloud-based technologies, such as remote workplaces and managed print services, are replacing old ways of conducting business. Cloud technology has been a significant game-changer for the office environment. Not only are files and documents stored on the cloud, but also businesses are using cloud-based platforms as a part of their services or customer experiences. Think about how much “software as a service” (a model in which software is licensed and accessed remotely instead of being downloaded on a user’s computer) has become a standardised part of doing business. This is all thanks to cloud technology. As time moves forward, expect it to continue making a significant impact on the modern workplace and customer experience. 2. Invest in voice-activated devices Various well-known gadgets found in "smart” homes or apartments are now making strides in the office setting, too. For example, voice-activated products such as Siri, Echo, Alexa, and Nest are commonly found in the workplace, adding functionality by offering a seamless user experience. Employees speak and the equipment automatically does what is asked — no more fiddling with equipment and trying to get things up and running manually. Voice-activated tech also allows workers to multitask and get things done faster, such as: Coordinating and syncing calendars Sending data requests Ordering supplies Reporting problems to the appropriate departments Streamlining IT requests These are just a handful of the many tasks voice-activated tech can perform. Businesses have steadily begun to include these types of products to make conference rooms even smarter. While this concept isn't mainstream in the office quite yet, it's not hard to image it becoming the norm within the next few years as this tech fully matures. Companies focused on modernising their workplaces are jumping on the proverbial bandwagon to get a leg up on the competition. These companies will be well ahead of the game when such tech initiatives do eventually become standard in the office. 3. Use tech to put offices in the comfort zone As modern offices evolve into open-space floor plans, they've become more informal and far more flexible. With that concept in mind, offices today are more focused on comfort — a stark contrast to the drab cubicle environments of yesteryear. Shifting to the open-design work environment has been a challenge for many; however, businesses are finding ways to make this transition easier through smarter tech. Solutions they are integrating into their spaces include: Hue lighting Virtual reality meeting rooms 360-degree video conferencing Keyless entry Smart tools not only appeal to workers because of their convenience and "coolness" factor; they also serve the practical purposes of enhancing comfort, personalising the remote experience, and even preventing repetitive stress injuries. 4. Integrate tech innovations to enhance the customer experience Businesses are investing in smart technology, and customers are reaping the benefits. As companies streamline their operations and customer service processes, customers are widely experiencing the convenience and simplicity associated with smart tech. Here are some features they currently enjoy: Chatbots for instant two-way communication AI-based customer learning opportunitiesPersonalised insights and recommendations Automation and custom ordering  Cloud storage of customer information and preference history Many industries are relying on artificial intelligence to improve their services. Businesses that do not offer this level of tech to customers will soon find themselves unable to meet heightened consumer expectations. 5. Use AI to gain a competitive advantage Perhaps you don't want to go as far as microchipping your employees (yes, this is also a growing trend) or issuing them Segways, but there are a lot of other relatively new gadgets and AI-driven tools that can boost the "smartness" of your business — not to mention, amp up your competitive advantage. For instance, you can use AI to track the habits and patterns of your customer base while they spend time on your website and determine where they are in their "customer journey" with your brand. Armed with this information, you can customise their web experience, along with your communications to them.  This personalisation can go a long way in your marketing efforts. After all, 80 percent of consumers say they are "more likely" to do business with a company that is able to give them a personalised experience. It's also important to know that research indicates customers want way more than basic personalisation. Using smart tech can easily help you bring things up to the next level. Smart tech adds significant value to the modern office in many ways. It's unwise to purchase tech because it's trendy, but when integrated with purpose and vision, many company decision-makers find this investment offers significant benefits and, in the end, pays off nicely. Harnham are the global leaders in Data & Analytics recruitment. Take a look at our latest roles or get in touch with one of our expert consultants to learn more.  

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