Senior Machine Learning Engineer

Button is building the future of the commerce powered internet — enabling performance marketing and monetization at scale across marketplaces, brands, and creators. We’re creating products that unlock new value at the intersection of discovery, engagement, and conversion. Button’s Mission is to empower the companies shaping the creator and affiliate economy - fueling mobile growth with innovation and new paths to monetization.  Our vision is an internet where all marketing is performance-based, everyone wins, and our innovation in the creator and affiliate economy lays the foundation for a new era of growth.

You'll own the end-to-end ML lifecycle: data and feature pipelines, training and evaluation, deployment, scoring, monitoring, and retraining. Working with PMs, data scientists, and software engineers, you'll turn ambiguous business problems into production ML systems, and build the infrastructure that moves models from research to production quickly while meeting standards for latency, scalability, cost efficiency, reproducibility, and safety. You'll work closely with our Data Teams and be central to how ML powers Button's commerce and monetization products.

• Own the full ML lifecycle, from feature pipelines and training workflows to deployment, inference services, monitoring, and retraining
• Design and build reliable data and feature pipelines, including feature store patterns that keep features reproducible and consistent across training, batch scoring, and online inference
• Build and optimize models for regression, classification, ranking, and recommender systems
• Implement and manage batch scoring pipelines and online inference services with clear performance, reliability, and latency standards
• Partner with data scientists to operationalize models and build tooling for consistent evaluation, experimentation, and iteration
• Collaborate with software engineers to integrate models into production services and APIs
• Establish observability for ML systems, including data freshness, feature drift, model performance, and pipeline health
• Design systems that support rapid experimentation and safe rollout of new models
• Document architecture, set ML engineering best practices at Button, and mentor teammates through code reviews and design discussions
• Contribute to the design of decisioning systems for ranking, recommendations, and commerce optimization

Minimum qualifications

• 5+ years of professional experience in ML engineering, software engineering, data engineering, or a similar role
• Fluency in Python and SQL
• Proven experience designing, building, and operating data pipelines at scale
• Hands-on experience deploying and maintaining ML models in production, not just training them
• A strong understanding of the full ML lifecycle, including feature generation, training pipelines, deployment strategies, and monitoring
• Experience building or working with feature pipelines or feature stores that support both training and online inference
• Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Experience in cloud environments, especially AWS
• Familiarity with orchestration and data modeling tools such as Airflow or dbt
• Clear, maintainable code with strong practices in testing, documentation, debugging, and system design
• Deep consideration for reliability, scalability, latency, and cost efficiency
• Comfort in ambiguous problem spaces and the ability to translate product questions into measurable ML solutions
• Enjoys close collaboration with engineers, data scientists, and PMs, and clearly communicates technical tradeoffs and design decisions

Preferred qualifications

• Experience building ranking, recommendation, or decisioning systems
• Familiarity with Amazon SageMaker, Redis, Spark, streaming systems, or distributed data processing frameworks

• Compensation: Base salary range of $153,000–$198,000. Final offer depends on skills and experience relative to the role's requirements.
• Comprehensive Health Coverage: 100% company-paid premiums for employee base medical coverage, with ~80% coverage for spouse, partner, and dependent care. Options include both traditional plans and a High Deductible Health Plan (HDHP) paired with a Flexible Spending Account (FSA) or Health Savings Account (HSA).
• HSA Company Contribution: For employees enrolled in the HDHP, the company contributes up to $1,800/year for individuals ($150/month) and up to $3,000/year for families ($250/month).
• 401(k) Retirement Plan: Automatic 3% company contribution starting after 30 days, completely independent of employee contributions and 100% vested immediately (with both traditional pre-tax and Roth options).
• Annual "Treat Yourself" Stipend: A $500 annual wellness and personal stipend to spend on vacations, spa days, personal electronics, or home goods.
• Monthly Tech & Connectivity Stipend: $130 per month ($1,560 annually) to cover cell phone and home internet expenses.
• Home Office Setup Allowance: A one-time $400 stipend for new hires to customize their workstation, equipment, and ergonomic office setup.
• Wellness & Fitness Perks: Subsidized fitness benefits, including discounted Peloton memberships ($10/month) and covered NYC bike-share memberships.
• Concierge Healthcare: Complimentary One Medical membership providing 24/7 on-demand virtual care and prioritized in-person appointments.
• Time Off: Unlimited time off (including your birthday), plus company-wide Mental Health Weeks
• Employee Assistance Program (EAP)
• RemotePlus workplace: Work from anywhere, with an NYC hub, WeWork All Access memberships in select markets, regular coworking days, and social events

Button is committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported and connected at work—regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives.

Button is an Equal Opportunity Employer. We do not discriminate against qualified applicants or employees on the basis of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by federal, state, or local law, rule, or regulation.