Senior Machine Learning Engineer

Button; United States; On-site; USD 153,000 - 198,000; Full time

Benefits offered by this job

Unlimited time off

401(k) with company match

Health insurance coverage

Lifestyle stipend

Monthly mobile phone stipend

Job summary

A leading technology company is seeking a Senior Machine Learning Engineer to manage the ML lifecycle, from data pipelines to model deployment. Collaborating closely with product managers and engineers, this role focuses on transforming complex business problems into effective machine learning solutions. The ideal candidate has experience in production ML systems, strong coding skills in Python and SQL, and is familiar with cloud environments, particularly AWS. This position offers a remote-friendly work environment with competitive compensation and benefits.

Qualifications

• 5+ years of experience in machine learning or data engineering.
• Proven record of deploying ML models in production environments.
• Experience with orchestration tools and data modeling.

Responsibilities

• Own the full ML lifecycle including training and deployment.
• Design and build data and feature pipelines for ML models.
• Collaborate with teams to operationalize models and improve performance.

Skills

Machine learning systems

Python

SQL

Cloud environments (AWS)

Data pipelines

Feature engineering

Scalable systems design

Education

Bachelor's or Master's in Computer Science or relevant field

Tools

TensorFlow

PyTorch

Amazon SageMaker

Airflow

Job description

Button’s mission is to empower the companies shaping the creator and affiliate economy - fueling mobile growth with innovation and new paths to monetization. Today, we work with some of the largest and most interesting businesses in the world to connect shoppers, creators, and retailers with what they love at the tap of a button. We build with the consumer experience in mind, have a reputation for paving the future of mobile, and have a good time doing it.

As a Senior Machine Learning Engineer, you will own the end to end ML lifecycle at Button, from the data and feature pipelines that feed models, through training and evaluation workflows, to deployment, scoring, monitoring, and retraining. You will work closely with product managers, data scientists, and software engineers to translate ambiguous business problems into reliable production ML systems that integrate with our platform and power real product decisions.

You will help build the infrastructure and patterns that allow models to move quickly from research to production while meeting real world requirements for latency, scalability, cost efficiency, reproducibility, and safety. This role works closely with our Data Teams and plays a central role in how machine learning powers Button’s commerce and monetization products.

AS A SENIOR MACHINE LEARNING ENGINEER, YOU WILL:

• Own the full ML lifecycle including feature pipelines, training workflows, model deployment, inference services, monitoring, and retraining.
• Design and build reliable data and feature pipelines, including feature store patterns that support reproducible training and consistent features across training, batch scoring, and online inference.
• Build and optimize machine learning models including 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 the tooling needed to run consistent evaluation, experimentation, and model iteration.
• Collaborate with software engineers to ensure smooth integration of models into production services and APIs.
• Establish observability for ML systems including monitoring of data freshness, feature drift, model performance, and pipeline health.
• Design systems that support rapid experimentation and safe rollout of new models.
• Document architecture clearly, establish best practices for ML engineering at Button, and mentor teammates through thoughtful code reviews and design discussions.
• Contribute to the design of decisioning systems that power ranking, recommendations, and commerce optimization across Button’s platform.

WE LOOK FOR TEAMMATES WHO:

• Write clear, maintainable code with strong software engineering practices including testing, documentation, debugging, and thoughtful system design.
• Have experience building and operating production machine learning systems rather than only training models.
• Understand the full ML lifecycle including feature generation, training pipelines, deployment strategies, and monitoring.
• Have practical experience designing scalable data pipelines and feature generation workflows.
• Have experience building or working with feature pipelines or feature stores that support both training and online inference.
• Think deeply about reliability, scalability, latency, and cost efficiency when building ML systems.
• Are comfortable working in cloud environments, especially AWS. Familiarity with Amazon SageMaker, Redis, Spark, streaming systems, or distributed data processing frameworks is a plus.
• Have experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Enjoy collaborating closely with engineers, data scientists, and product managers and can clearly communicate technical tradeoffs and design decisions.
• Are comfortable working in ambiguous problem spaces and translating product questions into measurable ML solutions.

EXPERIENCE LEVEL:

• 5+ years of professional experience in machine learning engineering, software engineering, data engineering, or similar roles.
• Fluency with Python and SQL.
• Proven experience designing, building, and operating data pipelines at scale.
• Hands on experience deploying and maintaining machine learning models in production environments.
• Experience working in cloud environments, especially AWS.
• Familiarity with orchestration and data modeling tools such as Airflow, dbt, or similar systems.
• Experience building ranking, recommendation, or decisioning systems is a plus.

Button provides employees with a RemotePlus workplace, which blends “work from anywhere” with in-person collaboration. Button has a “hub” workspace in New York City as well as team members distributed across the United States and beyond. The salary range for this role is expected to be between $153,000 - $198,000 (offered salary is based on a number of factors including skills and experience relative to the job description listed above).

In addition, Button provides employees with a 401(k) plan and automatically contributes 3% of an employee’s salary annually. We also want our employees to be well-rested and live balanced lives–Buttonians enjoy unlimited time off (including birthdays off) and periodic Mental Health Weeks which allow the entire company to take a breath and recharge, as well as an employee assistance program. For many of the health, vision, and dental insurance plans offered by Button, the company covers 100% of the premiums for employees and 75% for dependents. Button offers all employees and their dependents complimentary memberships to One Medical as well as a monthly stipend for mobile phone/internet and an annual lifestyle stipend. Button also offers employees in select markets “All Access” memberships to WeWork as well as regular “coworking days” and social events. Most of all, Button offers our employees the opportunity to live our company values–Grow & Learn, Experiment, Adapt, and Deliver–and to be a part of an incredible team of humans working together to build a better internet, fueled by commerce.

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.