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. And we’ve created a culture here that cares just as deeply about the career you’re building. Ours is a no ego culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of all those who 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 expect our teams to come together in our state-of-the-art office on two core days, typically Tuesday and Wednesday, to work together in person, and teams can choose where they work for the remainder of the week. We all benefit from flexibility and get to use the best of both worlds to get our work done.
Why are we hiring?Well, we’re growing and thriving. So, we need 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.
What You’ll DoWe are seeking a highly motivated and experienced embedded Machine Learning Engineer to join our growing Engineering team. As a key contributor, you will play a crucial role in developing and implementing cutting-edge machine learning solutions on embedded devices.
Primary responsibilities include:
- Support the deployment of ML models and systems on edge devices to solve real-world problems in the home security domain
- Take research initiatives in the embedded ML space 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) tradeoff for battery powered devices
- Stay up-to-date on the latest advancements in emerging techniques for 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
- Skilled in C++ and Python
- 3+ years of experience developing vectorized code on ARM using SIMD (Neon, Helium instructions)
- 8+ years of experience in developing production-grade machine learning solutions
- Strong understanding of deep learning architectures and statistical modeling techniques
- Experience with data preprocessing, feature engineering, and model evaluation.
- Excellent communication and collaboration skills
- Ability to work in a fast paced environment
- 3+ years of experience developing and deploying models on edge devices leveraging techniques for quantization such as QAT, PTQ
- Experience with relevant machine learning libraries (e.g., PyTorch TensorFlow, Keras)
- Experience with time series data
- Familiarity with cloud computing platforms (e.g., AWS, GCP)
- Customer Obsessed - Building deep empathy for our customers, putting them at the core of our work, and developing strong, long-term relationships with them.
- Aim High - Always challenging ourselves and others to raise the bar.
- No Ego - Maintaining a “no job too small” attitude, and an open, inclusive and humble style.
- One Team - Taking a highly collaborative approach to achieving success.
- Lift As We Climb - Investing in developing others and helping others around us succeed.
- Lean & Nimble - Working with agility and efficiency to experiment in an often ambiguous environment.
We wholeheartedly embrace and actively seek applications from all individuals, no matter how they identify. We are committed to cultivating a diverse and inclusive workplace, and we believe our work is enriched when we incorporate a multitude of perspectives, backgrounds, and experiences. We want everyone who works here to thrive and contribute to not only our mission of keeping every home secure, but also to making our workplace safe and supportive for others. If a reasonable accommodation may be needed to fully participate in the job application or interview process, to perform the essential functions of a position, or to receive other benefits and privileges of employment, please contact [email protected].
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SimpliSafe Boston, Massachusetts, USA Office
294 Washington Street, Boston, MA, United States, 02108
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