🔥 13 hours ago
Lead the development and deployment of production-grade machine learning systems, shaping architecture and engineering standards while advising clients and mentoring engineers.
Senior Software Development Engineer
🕒 yesterday
PythonAWS Sagemaker StudioSagemaker PipelinesTecton
📜 Description
- Design and maintain batch and real-time ML pipelines using SageMaker Pipelines, EventBridge, MLflow, and feature stores.
- Partner with data scientists, engineers, and stakeholders to implement and optimize model training, evaluation, drift detection, and deployment.
- Manage ML CI/CD, model promotion, retraining workflows, and integration across environments.
- Lead end-to-end delivery of ML features and mentor junior engineers on best practices.
- Participate in on-call rotations, incident response, post-mortems, and ML initiative planning.
🛠️ Requirements
- 5+ years in the software industry, including at least 3+ years in ML engineering, pipelines, or applied machine learning.
- Hands-on experience with AWS SageMaker Studio and Tecton; proficiency in Python and frameworks such as scikit-learn, PyTorch, or TensorFlow.
- Experience with MLflow, SageMaker Pipelines, EventBridge, and batch and real-time inference pipelines.
- Familiarity with Glue, EMR, or Flink for data preparation and feature pipelines.
- Understanding of ML CI/CD, model deployment, endpoint configuration, and validation; able to collaborate across Data Science, Risk, and Engineering.
- Additional experience with ensemble models, fraud or risk modeling, generative AI workflows, or Java, Scala, or Go is a plus.
✨ Benefits
- Paid time off
- Retirement savings plans
- Bonus or incentive eligibility
- Equity grants
- Employee stock purchase plan
- Health benefits
- Parental leave and other family-friendly benefits
Full job description
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 a GoDaddy 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 GoDaddy’s Commerce division. Partnering with the Data Science team, we support a wide range of machine learning and data engineering efforts that help GoDaddy 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 Bulgaria, 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...
- 5+ years in the software industry, with at least 3+ 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 encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.
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. GoDaddy’s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.
About us... GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy 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 GoDaddy, 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.
We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way.
GoDaddy is proud to be an equal opportunity employer. GoDaddy 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 can be helpful, please reach out to myrecruiter@godaddy.com.
GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.
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