Machine Learning Engineering Manager, Embedded AI

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About SimpliSafe We’re a high-tech home security company that’s passionate about protecting the life you’ve built and our mission of keeping Every Home Secure. We’ve created a culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of those we protect. We don’t just want you to work here. We want you to grow and thrive here. We’re embracing a hybrid work model that enables our teams to split their time between office and home. Hybrid for us means we come together in our state-of-the-art office on two core days, typically Tuesday and Wednesday, to work in person, and teams can choose where they work for the remainder of the week. Why are we hiring? We’re growing and thriving, and we’re looking for smart, talented, and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure. About the Role SimpliSafe is seeking a seasoned engineering manager with experience in the embedded machine learning space to join the Machine Learning team. As a key contributor, you will play a crucial role in developing and implementing cutting-edge machine learning models for a range of edge devices. Manage the edge AI team which is responsible for designing, developing, and deploying ML models to edge devices to solve real-world problems in the home security domain Work with key stakeholders to identify key research initiatives that can impact business outcomes Set the research direction/roadmap for model optimization techniques Take research initiatives from idea generation to production Plan, adapt and execute multiple initiatives independently and through others Collaborate with engineers and product managers to achieve optimal performance (accuracy vs. power consumption) tradeoffs for battery-powered devices Stay up-to-date on the latest advancements in model optimization techniques such as compression and quantization Contribute to the development of our machine learning infrastructure and tools Influence team culture and exemplify best practices in applied research Requirements MS or PhD in Computer Science, Artificial Intelligence, or a related field 8+ years of experience in developing production-grade machine learning solutions Experience managing an engineering team Strong understanding of deep learning architectures and statistical modeling techniques, especially as it relates to computer vision and natural language processing Skilled in Python and relevant machine learning libraries (e.g., PyTorch, TensorFlow, Keras) Skilled in C/C++ 3+ years of experience developing and deploying models on edge devices leveraging techniques for quantization such as QAT, PTQ Experience with data preprocessing, feature engineering, and model evaluation Excellent communication and collaboration skills Ability to work in a fast paced environment Nice to Have Experience with deep learning model architectures such as YOLO 3+ years of experience developing vectorized code on ARM using SIMD (Neon, Helium instructions) Experience with time series data Familiarity with cloud computing platforms (e.g., AWS, GCP) What Values You’ll Share Customer Obsessed Aim High No Ego One Team Lift As We Climb Lean & Nimble What We Offer A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families Free SimpliSafe system and professional monitoring for your home Employee Resource Groups (ERGs) that foster networking, mentoring, development, and advocacy Equal Opportunity We are an equal opportunity employer committed to a diverse and inclusive workplace. We welcome applications from all qualified individuals and do not discriminate on any protected status. If accommodations are needed during the application or interview process, please contact careers@simplisafe.com.
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Location:
Boston, MA, United States
Salary:
$250,000 +
Job Type:
FullTime
Category:
Engineering

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