Apply here: Machine Learning/AI Engineer at Skylyte
Skylyte is seeking a talented individual who possesses infinite curiosity, resourcefulness and optimism. You’ll partner with our Founding CTO and co-founders to create groundbreaking technology that has the potential to change how teams interact. This is an incredible opportunity to make a meaningful impact on the future of how teams operate.
Skylyte is a fast-growing B2B startup, started by two Stanford alumnae. In the midst of the secondary pandemic of ‘mental health at work’, we are rethinking team health and resilience by utilizing big data, smart coaching and behavior change. Our science-driven tools equip teams with the ability to prevent burnout in order to stay at peak performance. We’ve have worked with high-intensity industries and companies including Stanford Hospital, NASA, amongst others and are part of the Mayo clinic protocol on burnout prevention.
Eventually we plan to become teams’ trusted digital GPS for all people matters. In an increasingly remote work, we want to revitalize the workplace, one team at a time.
Our team thrives on open, direct communication and feedback, a shared growth mindset and desire to learn and improve, and a passion for turning some of the world and workplace’s toughest challenges into opportunities.
We are seeking a driven, full-time machine learning engineer to help us leverage employee data related to team burnout and resilience. As one of the first hires in the company, you will be working directly with the founding team to help develop novel solutions.
You will own all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
This role places you to be in a strategic position to influence future roadmaps for AI-driven features and products. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.
- Design, develop, and deploy deep & machine learning applications using complex high dimensional signals.
- Establish and improve learning loops for AI systems to drive continuous improvements.
- Develop scalable solutions that can work in real-time with large amounts of data.
- Optimize and automate model training and testing for experimentation, development, and production.
- Lead short-term projects with a direct impact in the product.
- Stay on top of academic research to identify methods we should integrate.
- Professional experience in deep learning methods for cross-modal signals (text, audio, video, etc)
- Strong technical knowledge of classical machine learning approaches as well as novel deep learning methods
- Experience deploying production-grade AI applications.
- Proficiency with deep learning frameworks such as TensorFlow/Keras or PyTorch as well as packages for machine learning such as scikit-learn and pandas.
- Ability to know when to resort to 3rd-party models and APIs and when to build proprietary solutions.
- Problem-solving (‘can do’) mindset
- Constant need to learn (‘infinite curiosity’) and overcome the barriers of technology.
- Genuine team spirit and a deep passion for our mission.
- Experience in early-stage tech, ability to be flexible and to adapt to rapidly changing priorities
- Experience with chatbot platforms, such as Google Dialogflow, Amazon Lex, Microsoft Azure Bot Service, or IBM Watson Assistant.
- Experience with computer vision image synthesis and classification
- Experience in monitoring and performance analysis of Machine Learning AI and GPU server platforms
- Autoscaling, containers, performance tuning and optimization