- Gain knowledge in the relevant domain (e.g.appliance signatures, failure modes, load disaggregation)
- Feature engineering (including embedded implementation)
- Use your experience with different machine learning frameworks to identify suitable tools for integration in Span's software platform
- Integrate developed algorithms in our production code base with robust test coverage
- Work with the firmware and software teams to design Span's edge model deployment framework
- Proactively identify opportunities within Span that can benefit from data science analysis
- Use fleet data to monitor algorithms in the field
- Guide selection of hardware for next generation products and recommend ways to future-proof our designs
- Master's degree or higher in Computer Science, Mathematics, Engineering, or a closely related field
- 5+ years' of professional experience with developing and implementing machine learning models in production for a IOT / hardware related product ; 7+ years of overall experience
- Deep understanding machine learning algorithms (feature extraction from high-frequency signals, ML for physical processes, model compression and edge inference)
- Advanced Python skills, as well as familiarity with pandas and various ML toolkits (pytorch / tensorflow)
- Software design experience and ability to write clean, maintainable, and shippable production code
- Experience working with SQL and data visualization tools
- Extensive data modeling and data architecture skills
- Knowledge and experience working within cloud computing environments such as AWS
- Strong communication and interpersonal skills
- Ability to understand and explain complex problems simply and effectively
- Exposure to digital signal processing as applied to feature extraction and processing
- CUDA programming / distributed training methods
- Experience in non-intrusive load measurement methods
- Blind source separation techniques including ICA / PCA / EMD
- Understanding of electrical systems and residential loads
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Staff Machine Learning Engineer - San Francisco, CA, United States - Span
Description
The Role
We aim to establish the Span panel as the center of home energy andthe backbone of the renewable distributed grid. Analytics and ML are essential tools to develop features for the smart, green, energy-efficient home of the future. Span's unique ability to monitor and control individual circuits opens up a new avenue for proactive whole-home management and equipment failure detection. As Staff ML Engineer, you will leverage your deep understanding of ML, modeling, and statistics to solve problems including anomaly detection, event prediction and context understanding with the goal to optimally manage whole-home energy consumption, deliver meaningful insights to the customer, and notify them about a potential failure of equipment or hazards in their home. You'll spearhead the entire development process, from working with the product team to define scope, the the firmware team to assess what can be implemented, the cloud team on ML ops, and the data collection team for training data. That said, we are a startup - broad range of production software development skills, flexibility to wear many hats, and enthusiasm to learn will go a long way.
Responsibilities
Lead the development of ML algorithms from the ground up which includes:
Note: We're a startup, so while this list is broad, it's still just a start; you'll end up wearing many hats during your time at Span.
About You Required Qualifications
Bonus Qualifications
The U.S. base salary range for this position is $190,000 - $225,000 plus benefits, equity and variable compensation for Sales-related roles. This range represents SPAN's good faith estimate of competitively-priced salary for the role based on national, real-time industry data from companies of a similar growth stage. This range reflects minimum and maximum new hire salaries for the role across US locations. Within the range, individual pay is determined by location and individual factors including relevant skills, experience and education or training. This range correlates to the relative level of the candidate we believe we need for the role and may require an adjustment for candidates of a different level.
Your recruiter can share more about the specific salary range for the location this role is based during the hiring process.
Life at SPAN
Headquartered in San Francisco's vibrant SoMa neighborhood, we are an eclectic group of creative thinkers who value open communication, teamwork, and a 'make it happen' approach to addressing complex challenges.
SPAN embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
We're hiring talented individuals who are driven by success and are passionate about shaping the future of renewable energy. If that sounds like you, we'd love for you to consider joining the rapidly growing team at SPAN.
The Perks:
Competitive compensation + equity grants at a well-funded, venture-backed company
Comprehensive benefits (including medical; dental, vision, life and disability insurance)
Comfortable, sunny office space located near BART and Caltrain public transit
Strong focus on teambuilding and company culture (events, meet-ups, clubs)
Flexible hours and unlimited PTO
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