Senior Machine Learning Engineer

Who We Are

Babylist is the leading registry, e-commerce, and content platform for growing families. More than 9 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, trusted guidance, and expert product recommendations for new parents and the people who love them. What began as a universal registry has grown into a full ecosystem for new parents, including the Babylist Shop, Babylist Health, and a flagship showroom in Los Angeles. Hundreds of brands in baby and beyond partner with Babylist to engage meaningfully with families during one of life’s most important transitions. With over $1 billion in annual GMV, and more than $500 million in 2024 revenue, Babylist is reshaping the $320 billion baby product industry. We’re helping parents feel confident, connected, and cared for at every step. As we build the generational brand in baby, our mission remains simple: to connect growing families with everything they need to thrive.To learn more, visit www.babylist.com.

Our Ways of Working

Babylist thrives as a remote-first company, with HQ team members located across the U.S. and Canada. We meet in person twice a year—once as a company and once by department to strengthen the relationships that power our work. We show up consistently, stay purpose-driven, and achieve results —together, from anywhere.

Our Tech Stack

• React
• Ruby on Rails
• AWS
• Sidekiq
• MySQL
• Redis
• Native iOS and Android

What the Role Is

As Babylist’s Senior Machine Learning Engineer, you’ll be the founding expert driving the next era of our machine learning and personalization efforts. This high-impact position is designed for a hands-on engineer—someone who builds, iterates, and productionalizes ML solutions that directly improve user experience and business outcomes.

You’ll lead technical development within a focused product pod (Product Manager, Software Engineer, occasional Designer), architecting the models behind our homepage feed, “add next” experience, and more. Reporting to our Senior Manager of Data and Analytics Engineering, you’ll help define how advanced recommendations and AI power our platform.

Who You Are

• You are excited to design, build, and optimize recommender systems that improve product and content discovery for millions of Babylist users
• You have hands-on experience taking machine learning models from prototype to scalable, production-ready deployments
• You thrive at the intersection of product, data, and engineering, and you enjoy identifying high-value personalization opportunities that drive measurable business impact.
• You are comfortable working in a small, agile pod while also helping shape the broader ML strategy across the organization
• You take ownership of the full ML feature lifecycle—from framing problems with stakeholders to deployment, monitoring, and iteration
• You value robust, well-documented data sets and are excited to advance Babylist’s personalization infrastructure without heavy data-cleanup overhead
• You bring deep expertise in SQL and Python for machine learning applications.You have a proven track record of delivering production-grade ML solutions, ideally in recommender systems, personalization, or similar consumer-facing products
• You understand the ML lifecycle end-to-end: experimentation, validation, rollout, and monitoring
• You have experience with distributed training frameworks, workflow orchestration (e.g., Airflow), and model monitoring tools
• You bring relevant domain experience from consumer products such as e-commerce, dating apps, or platforms with complex user journeys
• You are highly autonomous, able to define problem spaces, architect solutions from zero to one, and operate with strong ownership
  

How You Will Make An Impact

• Establish Babylist’s first machine learning function—defining the roadmap, practices, and long-term vision for personalization at scale
• Translate complex data into high-leverage personalization features that directly improve product discovery, user engagement, and business outcomes
• Accelerate experimentation and deployment by leveraging Babylist’s mature data infrastructure and close partnerships with analytics, engineering, and product leaders
• Deliver high-impact ML systems end-to-end, from design to production, with clear visibility into results for millions of users
• Shape Babylist’s ML culture by setting technical standards, mentoring peers, and influencing the organization’s broader AI strategy

Why You Will Love Working At Babylist

• We invest in the infrastructure you’ll need to be supported and successful: tools, opportunities to connect with colleagues, and a stipend to help you set up your office
• We build products that have a positive impact on millions of people’s lives
• We work at a sustainable pace which means work/life balance is a real thing here
• We believe technology and data can solve hard problems 
• AI plays a meaningful role in how we work, create, and scale—intentionally embedded in our tools, systems, and decision-making to support innovation and real impact
• We believe in exceptional management 
• We offer competitive pay and meaningful opportunities for career advancement
• We have great benefits like company paid medical, dental, and vision, a generous paid parental leave policy, and 401k with company match
• We care about employee wellbeing with perks for physical, mental and emotional health, parenting, childcare, and financial planning

Babylist follows a market-based approach to compensation, with pay varying based on location, experience, and qualifications. In compliance with applicable pay transparency laws, the starting salary range for this role is $157,617.00 to $236,467.00, representing the lowest to highest compensation we reasonably expect to offer for this position.

Your starting salary within this range will be determined based on your skills, experience, and work location, with future adjustments informed by role growth, performance, and internal pay equity. Babylist is committed to supporting career progression and recognizes the value of performance-based advancement.

In addition to competitive pay, Babylist offers equity, bonus opportunities, and a comprehensive benefits package, including company-paid health, dental, and vision insurance, 401(k) matching, flexible spending accounts, and paid leave, including PTO and parental leave.

Interview Process & Data Use
To support a fair and consistent hiring process, Babylist uses AI to transcribe all interviews. Transcripts are confidential and used solely for evaluation purposes, in accordance with data privacy laws such as CCPA and GDPR. By applying, you acknowledge and consent to this use.

Interview & Education Integrity
To ensure fairness, we require that all technical interviews and assessments be completed independently and without assistance from AI tools, bots, content-farming services, or real-time coaching platforms (e.g., ChatGPT, GitHub Copilot, Interview Warmup, etc.) Any indication of third-party help or AI-generated responses—including real-time AI coaching or farming of answers— will result in immediate disqualification. We may also verify degrees and academic records through third-party sources. Providing false information will result in removal from our interview process.

Official Communication
All communication regarding your application will come only from the Babylist Talent Team via an @babylist.com email address. We will never request payment, bank information, or personal financial details. Be cautious of fraudulent outreach via non-company email addresses, messaging platforms (e.g., WhatsApp, Telegram), or unsolicited phone calls. To verify legitimate opportunities, visit our careers page.

SMS Consent
As part of our hiring process, you may be offered the option to receive text message updates about your application or interviews. Opting out will not affect your application status—communication will continue via email or phone. Message and data rates may apply. You can reply STOP to unsubscribe or HELP for assistance. See our Privacy Policy for more information.