As life changes, people want to maintain their independence, individuality, and freedom to keep living life confidently and on their terms. Caregivers want confidence that their loved one will be safe, and confidence that those receiving care will have help when they need it.
Nomo Smart Care offers caregivers a way to know how their loved one is doing and if they need help even when they can’t be there, all while allowing the loved one to keep their independence. We do this with a focus on customizable privacy options. We’re not a huge tech company here for data. We’re not looking to sell complicated features.
At Nomo, we are caregivers too. As a family-owned organization made up of a diverse mix of employees and partners, we offer simple, intelligent, and connected tools to help caregivers support their loved ones’ independence while answering the question, “How’s Mom?”.
Nomo Smart Care™ - Know More, Worry Less. ™
The Role
The primary function of the Machine Learning Engineer is to define processes, establish infrastructure, and contribute to enhancing the Machine Learning capabilities of the organization from the ground up. This includes creating, improving, and deploying ML models in an embedded environment, particularly focusing on applications like vision and audio classification. The Machine Learning Engineer will be responsible for software development, optimizing hardware and infrastructure, designing data pipelines, and implementing robust AI solutions for real-world use cases. The role also involves a strong emphasis on driving projects from inception to production and delivering impactful solutions that contribute to customer success.
What You'll Do
As a Machine Learning Engineer, you will be a driving force in shaping our ML infrastructure and capabilities. Your responsibilities will encompass:
- Defining processes and best practices to establish the Machine Learning infrastructure at Nomo, contributing to the evolution and enhancement of our ML capabilities.
- Creating, enhancing, and deploying ML models within an embedded environment.
- Developing and deploying ML solutions on embedded devices, spanning diverse application areas such as vision and audio.
- Engaging in software development, optimizing infrastructure and hardware, designing data pipelines, and innovating to implement robust AI solutions for real-world use cases.
Requirements
- Strong software development skills, with proficiency in relevant programming languages and AI/ML frameworks (e.g., Python, TensorFlow Lite).
- Hands-on experience in successfully shipping machine learning-based projects into production and delivering tangible impact to customers.
- Solid domain knowledge in vision and audio classification, showcasing your expertise in these specific areas.
- A high level of motivation, coupled with strong communication skills. You should be driven to lead projects from concept to production.
- Excellent verbal and written communication skills in English.
Extra Credit
While not mandatory, possessing the following qualifications will be a significant advantage:
- Experience in creating and deploying TFLite models on ESP32 devices, demonstrating your ability to work with specific embedded hardware.
What We Offer
- A fun and supportive team culture
- Opportunities for professional growth and development
- Access to the latest tools and technologies
If you're excited about shaping the future of Machine Learning, driving innovation, and delivering impactful solutions, we encourage you to apply and be part of a team committed to pushing the boundaries of technology. Apply now by sending us your resume and a cover letter explaining why you are the perfect fit for this role. We can't wait to hear from you!
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