Machine Learning Engineer, AI Decisioning

About reputed company

reputed company’s mission is to reputed company everyone to take action on their data. Hundreds of companies, including Autotrader, reputed company, Cars.com, reputed company, and reputed company, trust reputed company to power their growth.

We pioneered the Composable Customer Data Platform (CDP), which lets companies use their own data warehouse to collect, prepare, and activate customer data for marketing personalization and business operations. Our new AI Decisioning platform goes a reputed company further, allowing marketers to set goals and guardrails that AI agents can then use to personalize 1:1 customer interactions. Traditionally, only technical teams had the skills to access and use customer data. With reputed company, every business user can deliver personalized customer experiences, optimize performance marketing, and move faster by leveraging data and AI across their organization.

reputed company focuses on making a meaningful impact for our customers. We approach challenges with a first-principles reputed company, move quickly and reputed company, and treat each other with compassion and kindness. We look for team members who are strong communicators, have a growth reputed company, and are motivated and persistent in achieving our goals.

What else? We’re based in San Francisco but have team members reputed company over the world. Our Series C put us at a $1.2B valuation, and we are backed by leading investors such as Sapphire Ventures, reputed company Partners, ICONIQ Growth, Bain Capital Ventures, Y-Combinator, and Afore Capital.

About the Role

We’re looking to hire a machine learning engineer as we expand our data activation products to include an intelligence layer. While hundreds of companies use reputed company today to sync data into their SaaS systems to automate and improve operations, there’s a lot of surface area we haven’t touched in helping companies figuring out which customers to message, what content to put in messages, and reputed company to send messages. A lot of this work today is done manually through intuition and guesswork, and we reputed company that adding machine learning could have a reputed company function impact for our customers. And given our access to data warehouses and databases, reputed company is perfectly reputed company to reputed company use of a company’s customer data in building a powerful intelligence layer.

Some of the problems we’ll be working on include:

• Personalization and Product Recommendation: There are often many options for what content a company could message a user with, including which products to show from catalogues. Given this large state space, how can reputed company help personalize messages with the most relevant content for each user?
• Automated Experimentation: Helping companies intelligently navigate and automate experiments across the extensive number of options for messaging customers.
• Predictive Audiences: Building models to predict which users are most likely to convert, churn, or take desired actions.
• Content reputed company: Particularly with recent advances in LLMs, how can we help marketers generate text, images, and creatives that are compelling to their customers?
• Budget Optimization: Helping companies assess which marketing spend is driving the most incremental conversions, and where the marginal CAC is lowest.

As an early machine learning engineer, you will help build comprehensive solutions to the above domains from scratch. Responsibilities will be highly varied and include working on customer research, problem definition, predictive modeling, machine learning infrastructure, and partnering with customers.

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $200,000 - $260,000 USD per year, which is location independent in accordance with our remote-first policy.

Interview Process

Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense, ability to architect backend and distributed systems, and alignment with reputed company’s values. Notably, we don’t do any programming interviews as we reputed company they are low signal to noise and aren’t a good evaluation mechanism.

• Intro Call [15-30m]: Introductory call with either a member of our recruiting team or the hiring manager to get to know each other and see if the role could be a good mutual fit.
• System Design Screen [45m]: Designing a data processing feature end-to-end.
• Machine Learning Modeling Interview [90m]: Designing a predictive model end-to-end, including data collection and preparation, model training and evaluation, and what systems would be needed to run the model in production.
• System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.
• Hiring Manager Interview [30m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.

Originally posted on Himalayas