Machine Learning Engineer
Signet Jewelers
full-time
Posted on:
Location Type: Office
Location: Akron • Ohio, Texas • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSDockerETLJenkinsKubernetesPandasPySparkPython
About the role
- Design, build, and automate production-grade data pipelines to support elasticity, uplift, and other analytical models
- Implement clean, reusable data transformation logic that ensures consistency across modeling, analytics, and reporting layers
- Develop and maintain real-time inference services (e.g., AWS SageMaker endpoints) to allow business teams and applications to consume model outputs seamlessly
- Establish MLOps best practices, including: Model performance monitoring and drift detection, Automated retraining and evaluation pipelines, Feature/model versioning and lineage tracking
- Enable CI/CD for ML deployments, ensuring reliability, reproducibility, and rapid iteration
- Partner with Data Science teams to accelerate experimentation and automate recurring workflows
- Identify and drive automation opportunities across the broader AI & Data Science ecosystem to improve scalability, reliability, and cost efficiency
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Applied ML, or equivalent experience
- 3–6 years of industry experience in ML Engineering or MLOps
- Experience in retail analytics — such as demand forecasting, pricing, promotions, inventory optimization, customer segmentation, or e-commerce metrics — is highly preferred
- Strong programming skills in Python (pandas, PySpark, FastAPI, etc.)
- Experience building and managing ETL/ELT pipelines
- Hands-on experience deploying ML systems on AWS (SageMaker, Lambda, ECS/EKS, S3, Kinesis/Streams, etc.)
- Experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins, etc.)
- Familiarity with monitoring and observability for ML (model drift, feature drift, inference latency, cost monitoring)
- Experience with containerization & orchestration (Docker, Kubernetes) is a plus
- Experience building data products or ML-powered APIs that expose predictions or insights back to business applications is nice to have.
- Experience supporting batch + real-time inference workloads
Benefits
- Comprehensive healthcare, dental, and vision insurance to keep you and your family covered
- Generous 401(k) matching after just one year to help secure your financial future
- Ample paid time off, plus seven holidays to recharge and unwind
- Exclusive discounts on premium merchandise just for you
- Dynamic Learning & Development programs to support your growth
- And more!
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data pipelinesdata transformationreal-time inference servicesMLOpsmodel performance monitoringautomated retrainingCI/CDETLPythoncontainerization