Machine Learning Engineer

Clutter is an on-demand technology company based in Los Angeles that is disrupting the $50B/year self-storage and moving industries. We’ve built an end-to-end logistics and supply chain platform that enables us to offer consumers a much more convenient solution at price parity with the incumbents. We’ve raised $300M from a number of VCs including SoftBank, Sequoia, Atomico and GV (formerly Google Ventures). We have 500+ team members and tens of thousands of customers in 8 major markets across the US with plans to be in 50+ markets, domestically and internationally, within the next 5 years!

At Clutter, we're fortunate to be providing a consumer value proposition that people love and one that makes economic sense - a true product/market fit that few startups ever find. To deliver on our promise to consumers, team members and investors, we're focused on hiring, training and retaining exceptional individuals. This means that we have a very thorough interview process and maintain high performance expectations, but we'll always be transparent with you and respectful of your time.

The opportunity:

As a Senior Machine Learning engineer at Clutter, you will build and deliver business critical ML and Operations systems - the foremost of which is our Pricing Engine. You will have the opportunity to build our dynamic pricing system from the ground up, so as to hit key business targets such as user growth, revenue etc. This includes everything from developing, tuning and deploying algorithms to working closely with Data Science and business collaborators across the board. You are energized by driving business impact, delivering lift on top-line KPIs, and you thrive in a fast-paced environment.

As a Senior Machine Learning Engineer - you will:

• Build Clutter’s feedback-driven Pricing Engine to optimize a chosen set of objectives - user growth, revenue, etc. within a defined set of constraints.
• Architect and deliver the Pricing Service with monitoring, observability, analytics and performance in mind
• Work closely with data scientists to build and productionize pricing and other related algorithms - e.g. Marketing, Supply Chain forecasting etc.
• Partner with business stakeholders - Product, Finance and Operations to influence their KPIs using Pricing.
• Develop capacity, time-series and other forecasting algorithms that impact pricing related KPIs
• Analyze user and algorithm behavior to refine pricing strategy

What we're looking for:

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or similar
• Experience using machine learning to build optimization systems or feedback-driven systems
• Expertise with a programming language such as Java or C++, and an eagerness to learn more
• Experience with Python, R, and Matlab and proficiency in SQL
• Demonstrated track record of delivering business impact

Bonus Points if you have:

• Worked on other Dynamic Pricing systems
• Have experience with Control Systems, Bidding Systems and the like
• Ruby on Rails experience