Head of Product, OmniML
Director of Product
Office located in San Jose, CA
AI deployment platform for edge devices
Job no longer available
AI deployment platform for edge devices
1-20 employees
Job no longer available
Office located in San Jose, CA
1-20 employees
Company mission
To revolutionize the 250+ billion edge devices market with powerful AI deployment.
Role
Who you are
- Minimum of 5 years of proven experience leading product strategy through multi-phase growth, including from concept to launch
- Demonstrated ability to scale product development and a product ecosystem from the ground up; proven experience in design driven B2B technology products
- Strong communication skills, ability to discuss complex concepts with engineering as well as with marketing/sales and external stakeholders
- Able to work closely with the engineering team and clients to coordinate product and technical considerations
- Able to operate in a complex product environment with multiple stakeholders
Desirable
- Experience in SaaS, especially in machine learning/AI and edge computing area Experience in startups or high growth companies, or desire to work in a fast-paced, dynamic startup environment
- MBA with background in engineering
What the job involves
- Own the entire product experience: Define, own, and execute product roadmap
- Work with our CEO and CTO to manage engineering team priorities; partner with sales and marketing to define our products’ value proposition, understand product gaps and close them
- Define measurable goals, set priorities, lead a backlog of features and functionality, and work with the teams to meet those requirements
- Build out and grow a team of Product Managers while helping them to reach their potential
- Communicate with clarity the strategy, progress, and success to the entire company and external stakeholders
- Get things done!
Our take
Machine learning and AI is in higher demand than ever - the only issue is, it’s historically been limited, in general, to devices with larger computing power. This is a pain point, as we’re in a period where edge computing is developing and penetrating fast across many industries. This means there’s huge demand to bring complex computing like ML/AI to this smaller, lower-power hardware.
OmniML is looking to change this, with an award-winning platform that allows users to build, optimize, and deploy ML models on network edge hardware by compressing existing, but overly sized, AI models. By facilitating the creation of lightweight ML/AI, it should bring the autonomy, intelligence, and usefulness of larger computers to everyday devices without developers needing to manually adjust every AI model.
Whilst the company left stealth mode only recently, its platform is already in use in areas like video surveillance. As AI models develop and are more broadly adopted, the potential scope for OmniML’s platform is huge, encompassing most industries - but especially high-growth and lucrative ones like wearable tech and autonomous vehicles. AWS’ AutoML library and the PyTorch deep learning framework at Meta Platform are already incorporating facets of its tech, too, so whilst young, OmniML is causing a substantial stir.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (1 round)
Mar 2022
$10m
SEED
Total funding: $10m
Company benefits
- Competitive compensation package
- Medical, dental, and vision plans
- Generous PTO policy (vacation, bereavement, sick leave, jury duty, holidays)
- Yummy lunch
- Healthy (and some unhealthy) snacks and beverages
- Maternity and paternity leave policy
Company HQ
Kendall Square, Cambridge, MA
Leadership
Di Wu
(CEO)Previously the Director of Software Engineering at Falcon Computing Solutions. before taking up a Software Engineer role at Facebook.
Huizi Mao
(CTO)Completed a PhD in Electrical Engineering at Stanford, before taking up various internships at DePhi, Facebook, NVIDIA, and Google.
Song Han
(Co-founder)Completed a PhD on deep learning at Stanford, and is currently an Associate Professor at MIT.
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