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Senior Machine Learning Engineer

Cambridge, MA

Senior Machine Learning Engineer

Data ScienceTheale, England, United KingdomFull time

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Description

Join a leading green tech smart home scale up to help deliver on significant international growth potential, and make a measurable and lasting impact on global carbon emissions

Sense is on a mission to make all homes intelligent, and in turn more efficient, safer and reliable. Using the power of artificial intelligence, Sense can dramatically reduce a home's carbon emissions, with the potential to remove over one gigaton of carbon from the atmosphere every year.

Sense is backed by some of the largest companies and investors from the world of energy, AI, and technology. Our revolutionary machine learning technology has been recognised with numerous awards including:

  • Best Consumer AI Technology - AI Dev World
  • Global Cleantech 100
  • "One of the world's top 100 AI companies" - VentureBeat
  • Top 100 Red Herring
  • Clean Tech Company of the Year - NE VCA

Sense was founded in 2013 by pioneers in speech recognition technologies. This background provides the team with the intuition needed to connect and unlock key data significance relating to home energy efficiency.

Sense uses machine learning technology to provide real-time insights on device behavior. Customers rely on Sense for a wide range of uses including monitoring their home appliances, determining whether they left appliances running and identifying how to reduce their energy costs. Meanwhile, energy companies are able to more rapidly integrate energy renewables onto the grid with the insight and control that Sense brings.

We are now expanding internationally. Our strategy is to engage directly with partners in the energy, insurance, and home service industries and deliver our technology into millions of their customers' homes. We are now looking for extraordinary people to help us deliver on our exciting growth plans. We are building a new team in the UK. Benefiting from the support of HQ in Massachusetts, this team will be responsible for delivery and growth in all international markets

Requirements

Job Description

We are looking for a Senior Machine Learning Engineer to be the first member on our International Data Science team which will be based in Theale (M4 Corridor, 40mins from Paddington) in the UK. You will be working with our Boston-based DS team to develop machine learning models for detecting appliances, expand our growing fleet and team internationally, and modernise our data pipeline.

We are looking for someone who is:

  • Passionate about the energy sector and climate change.
  • Excited to expand Sense’s disaggregation platform internationally.
  • Eager to lead large-scale, real-world Machine Learning projects
  • Thrives in a young, fast-paced, and exciting startup.


What you'll do:

  • As the first Machine Learning Engineer in the Sense UK office, you will work closely with the DS team in the Boston office to architect and build a disaggregation platform for our users outside the US.
  • Lead projects to enhance and adapt the Sense load disaggregation platform to the challenges of different countries
  • Design and implement unsupervised dynamic algorithms that learn home-appliance models from wattage time-series and other signal representations
  • Dive into data, clean it up, and pull out insights that can be used to improve system performance
  • Drive successful algorithms to production
  • Contribute to the technical vision of Sense

What we're looking for:

  • Ph.D. degree in computer science, machine learning, statistics & applied mathematics, engineering (especially electrical engineering), physics, or similar fields
  • 4+ years of professional experience as a Machine Learning engineer
  • Excellent understanding of signal processing, time-series and frequency analysis, algorithms, and data structures
  • Strong problem solving and analytical skills
  • Experience with diving into data, finding insights, and presenting them
  • Solid Experience with programming in Python
    • comfortable with numpy, pandas, scikit-learn, and tensorflow
  • Knowledge of C/C++ is a plus
  • Experience with AWS services is a plus
  • Please only apply if you currently have the right to work in the UK. We are unable to sponsor visas at this time

Benefits

Why Sense

Join Sense and take the opportunity to use your expertise to be part of our mission to reduce global carbon emissions by making homes smart and more efficient. Our energy data and tools demystify home energy use, empower people to take command of their usage, and enable utilities to build a cleaner and more resilient grid.

  • Be a part of building something that will make a difference in the world.
  • Work with a small team of experienced entrepreneurs creating revolutionary technology.
  • A wide range of difficult and interesting problems to be solved.
  • Great opportunity to gain experience at a consumer smart home startup.

Benefits

  • Competitive compensation and benefits including a pension scheme
  • We have a hybrid working model designed to attract talented people from across the UK and beyond. Rather than a standard office, our collaboration space is based in Theale, near Reading. This location is in the heart of the M4 corridor with ready access to the motorway network, and yet just 40 mins from Paddington, one-stop from Reading station and Crossrail, and five minutes walk from Theale train station. On-site facilities include a gym and cafe. Enabled by great technology, each week the team will gather in Theale for two to three days a week, with the rest of the week operating remotely or perhaps taking advantage of a hot desk within our office network. With our hybrid model, we want to draw the most talented workforce from London to Bristol, and from Birmingham to Brighton.
  • Sense is an Equal Opportunity Employer. Ensuring a diverse and inclusive workplace where we learn from each other is core to Sense’s values. We welcome candidates with backgrounds that are traditionally underrepresented in tech, and we strive to foster an engaging, respectful and supportive community where everyone feels empowered to do their best work.

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