Senior Machine Learning Engineer

1 Month ago • 5 Years + • Research Development

Job Summary

Job Description

The Commerce Data & ML team powers intelligent and secure experiences for the Commerce division. This role involves partnering with Data Science to support machine learning and data engineering efforts, including fraud prevention and tailoring product experiences. You will build and maintain production ML Risk Models and collaborate on data-driven marketing. The team uses SageMaker Pipelines, Tecton, Glue, GitHub Actions, and MLflow for batch and real-time inference. As a Senior Machine Learning Engineer, you will build production-grade pipelines and scalable ML systems for fraud mitigation, customer insights, and AI-driven experiences.
Must have:
  • Design, build, and maintain robust ML pipelines for batch and real-time inference.
  • Collaborate with Data Scientists, Engineers, and stakeholders to implement, monitor, and optimize ML workflows.
  • Enhance and manage CI/CD pipelines for ML models, overseeing model promotion and retraining workflows.
  • Lead the end-to-end delivery of ML features from architecture to monitoring and iteration.
  • Support operational excellence by participating in on-call rotations and production incident response.
Good to have:
  • Experience building dual-model pipelines (NeuralNet + XGBoost) and evaluating ensemble performance.
  • Knowledge of business-aligned success metrics like recall, hit rate, false positives, and model drift thresholds.
  • Experience with fraud detection, risk modeling, or financial domains.
  • Familiarity with prompt engineering, LLM integration, and evaluation workflows for generative AI.
  • Backend or data engineering skills in Java, Scala, or Go.
Perks:
  • Paid time off
  • Retirement savings (401k, pension schemes)
  • Bonus/incentive eligibility
  • Equity grants
  • Employee stock purchase plan
  • Competitive health benefits
  • Family-friendly benefits (parental leave)
  • Employee Resource Groups
  • Support for entrepreneurs/side hustles

Job Details

Location Details:

Colombia, remote

At GoDaddy, the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) , and some work entirely remotely.

This is a remote position, so you’ll be working remotely from your home. You may occasionally visit an office to meet with your team for events or meetings.

Join Our Team

The Commerce Data & ML team is at the core of powering intelligent and secure experiences for the Commerce division. Partnering with the Data Science team, we support a wide range of machine learning and data engineering efforts that help Commerce understand its customers, prevent fraud, and tailor product experiences. We work closely with the Risk team to build and maintain production ML Risk Models, such as Transaction Risk Scoring and Merchant Risk Models. We also collaborate with the Growth team to enable data-driven marketing and customer segmentation through reliable pipelines and predictive models.

We’ve evolved a robust ML platform built on SageMaker Pipelines, Tecton feature store, Glue, GitHub Actions, and MLflow - with support for both batch and real-time inference. Also, recently, we’ve begun developing prompt engineering workflows for LLM-powered chatbots. As a Senior Machine Learning Engineer on the Commerce Data & ML team in Colombia, you will play a key role in building production-grade pipelines and scalable ML systems that support fraud mitigation, customer insights, and AI-driven experiences.

What you'll get to do...

  • Design, build, and maintain robust ML pipelines for both batch and real-time inference using tools such as SageMaker Pipelines, EventBridge, mlflow, and feature stores.
  • Collaborate with Data Scientists, Engineers, and stakeholders to implement, monitor, and optimize ML workflows—including model training, evaluation, drift detection, and deployment.
  • Enhance and manage CI/CD pipelines for ML models, oversee model promotion and retraining workflows, and ensure seamless integration across different environments.
  • Lead the end-to-end delivery of ML features from architecture and implementation to monitoring and iteration, while guiding and mentoring junior engineers and promoting best practices.
  • Support operational excellence by participating in on-call rotations, production incident response, post-mortems, and contributing to the planning and scoping of ML initiatives.

Your experience should include...

  • 7+ years in the software industry, with at least 5 years focused on ML engineering, pipelines, or applied machine learning.
  • Hands-on experience with AWS SageMaker Studio, Tecton, and proficiency in Python and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).
  • Experience with experiment tracking (MLflow), orchestrating ML workflows (SageMaker Pipelines, EventBridge), and building/monitoring both batch and real-time inference pipelines.
  • Familiarity with data preparation and streaming tools (Glue, EMR, Flink) for feature pipelines.
  • Solid understanding of CI/CD for ML (model deployment, endpoint configuration, validation) and strong cross-functional collaboration skills with Data Science, Risk, and Engineering teams.

You might also have...

  • Experience building dual-model pipelines (e.g., NeuralNet + XGBoost) and evaluating ensemble performance.
  • Knowledge of business-aligned success metrics like recall, hit rate, false positives, and model drift thresholds.
  • Experience with fraud detection, risk modeling, or financial domains.
  • Familiarity with prompt engineering, LLM integration, and evaluation workflows for generative AI.
  • Backend or data engineering skills in Java, Scala, or Go (nice to have).

We've got your back...

We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits, including parental leave. Benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups. Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way.

About us...

empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us.

At, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences, and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion, and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report, which can be found on our Diversity Careers page.

is proud to be an equal opportunity employer. will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com.

doesn’t accept unsolicited resumes from recruiters or employment agencies.

Apply Now and Join the #GoDaddyLife today!

Please review these directions prior to submitting your application:

  • To ensure we address you correctly throughout the process, please enter your Preferred Name if different than your Legal Name. We may ask you to confirm your Legal Name at a later stage when necessary.
  • If you do not have a legal first name, please input FNU where you are asked to input your first name.
  • If you do not have a legal last name/surname, please input LNU where you are asked to input your last name/surname.
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  • For phone number, please enter your mobile number.

Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

Massachusetts Residents: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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