Backend Team Lead
Nanit is the first smart monitor to merge computer vision with data-backed sleep science, to produce the most advanced and secure camera technology ever introduced to the home. Nanit is combining computer vision, machine learning, and advanced camera sensors to measure a baby's sleep cycle by providing actionable insights that lead to improved sleep for the entire family. We are a dynamic VC-backed startup with proven products, marquee investors and a terrific team of people.
If you have a solid background in Software Engineering, high interest in AI systems in production and the passion to build great systems that help hundreds of thousands of parents (and their babies) around the world - this is the right place!
What will you do:
- Managing and leading SW developers focusing in the fields of Backend and AI-infrastructure/MLOps.
- Responsible for the team roadmap, team building and execution of SW projects in the group.
- Close work with the Algorithms and Data teams, solving together cutting edge real world problems
- Promote Software Engineering & System Design best practices, methodologies and toolset.
- Design and implement AI services for new Nanit features that use Deep Learning models and Computer Vision algorithms.
- Collaborate with ML Engineers to research, develop, deploy and monitor Machine Learning models at large scale.
- Design and implement MLOps, Data Pipelines and Big Data supporting solutions.
- Lead scale-up projects and technical research in the AI Group.
If this sounds like you, you probably have:
- At least 5 years of experience in Software Engineering.
- 0-2 years of experience in leading SW teams.
- B.Sc Computer Science / Software Engineering or related field.
- Experience working on high scale production-grade projects on a cloud platform (preferred: AWS)
- Strong programming skills in at least one programming language (preferred: Python).
- Strong ability to self-learn and come up with solid solutions to problems.
- Passion for writing clean, robust code and applying Software Engineering best practices.
Nice to have:
- Experience with MLOps: training, testing, deployment, and monitoring Machine Learning models in Production
- Experience with DevOps / TensorFlow / PyTorch
- Knowledge in Computer Vision and Machine Learning
- Experience with Data Engineering and Big Data Pipelines
- We have an awesome product that makes life a little more manageable for new parents.
- We work hard. We are constantly striving to discover new and innovative ways to improve our product and ourselves.
- We invest in people. We consider each employee a long-term investment and we see value in continuously nurturing and training them.
- We believe in creating a fun, ego-less, family friendly, flexible work environment.