Head of Machine Learning
SF Bay Area
YotaScale is the pioneer in AI-powered Cloud Infrastructure Management. It empowers CloudOps and DevOps engineering teams to effectively optimize around cost, performance, and availability considerations in real time. As the Head of Machine Learning, you will build, manage and own our entire ML platform and pipeline. You'll partner with engineering leadership to integrate Machine Learning in every aspect of our solutions. In this role, you will directly shape the future of the company by helping us define and execute on our product direction. We have many interesting ML problems to work on, and an amazingly talented engineering team that we are continuing to build out to tackle these challenges. Join us on this exciting journey as we build the future of cloud infrastructure with the latest breakthroughs in artificial intelligence.
The organization: ML Engineering
The Machine Learning team's mission is to build, evolve and scale the algorithms that power Yotascale's products. The team charter is (1) research, develop, improve and deploy new state-of-the-art algorithms and technologies that are the foundation of Yotascale's product suite; (2) help envision new products and novel uses for Yotascale technology; and (3) make it easy for other engineering teams to bring the power of machine learning to their work.
- Develop machine learning applications for real-world customer problems
- Lead the Machine Learning Team to design, code, train, test, deploy and iterate on large-scale machine learning systems
- Provide an expert perspective on ML/AI related strategy, tactics, and issues across the organization
- Participate in the architectural design of engineering platforms to improve ML capabilities across engineering and product
- Develop presentations and technical discussions to communicate broadly across Yotascale and customers
- Able to develop and review code in Python/Scala/R or other applicable technologies
- Present at broad industry conferences, forums, and publish in renown journals is a big plus
- Set and maintain a high-quality bar in hiring, models, code, and process
- Bachelors, MS or Ph.D. in Computer Science, statistics, Artificial Intelligence, Software Engineering, or other quantitative fields.
- 5+ years of professional experience in the areas of developing and deploying quantitative models, machine learning solutions for Anomaly Detection, Time-series analysis, and Forecasting
- 3+ years of experience as a lead ML engineer. Experience managing teams of data scientists, engineers, and quantitative modelers is a big plus
- Extensive experience with machine learning tools and libraries including Scikit-learn, Tensorflow, Keras.
- Experience with implementing ML solutions using services provided by Amazon Web Services or Google Cloud Platform is a big plus
- An inherent drive to solve problems, collaborate with others and mentor team members
- Meticulous and detail-oriented
- Ability to thrive in a fast-paced, high-growth, ever-changing startup environment
What We Offer
- Smart, engaged co-workers who are at the top of their game
- Solve problems for real customers with global name recognition
- Excellent Medical, Dental & Vision Insurance benefits for little cost to employees and their family
- Save money for retirement by participating in our 401K
- Proactive learning and teaching opportunities via individual book allowances, tech talks, and brown bag lunches
- Weekly catered lunches
- Team outings and bi-weekly company happy hours
- Great Menlo Park location close to the Caltrain station, Dumbarton bridge, Hwy 101, Palo Alto downtown and Stanford University