Mlops Engineer In Retail Resume Example
Professional ATS-optimized resume template for Mlops Engineer In Retail positions
John Doe
Senior MLOps Engineer | TechRetail Inc., New York, NY
Email: example@email.com | Phone: (123) 456-7890
PROFESSIONAL SUMMARY
Results-driven MLOps Engineer with over 6 years of experience specializing in deploying, managing, and optimizing machine learning models within retail environments. Adept at creating scalable ML pipelines, automating model monitoring, and integrating AI solutions into omnichannel platforms to enhance customer engagement and operational efficiency. Skilled in collaboration with cross-functional teams to deliver high-impact solutions aligned with business objectives and industry best practices. Passionate about leveraging emerging MLOps tools and cloud-native technologies to enable rapid innovation and continuous delivery.
WORK EXPERIENCE
June 2022 – Present
- Engineered scalable ML pipelines deploying over 50 models for personalized product recommendations, achieving a 15% uplift in conversion rates.
- Automated model retraining with CI/CD workflows, reducing deployment cycle time by 40%.
- Integrated real-time monitoring using Prometheus and Grafana, resulting in a 20% decrease in model drift issues.
- Led the migration of ML workloads from on-premise infrastructure to AWS SageMaker, ensuring compliance and cost efficiency.
- Collaborated with Data Science teams to develop version control strategies and model lineage tracking using MLflow.
*MLOps Engineer | RetailData Solutions, Chicago, IL*
March 2019 – May 2022
- Developed end-to-end deployment pipelines for customer segmentation models, reducing manual intervention by 60%.
- Established automated testing frameworks for validation of models before production rollout.
- Managed Dockerized environments harmonized with Kubernetes to ensure consistent deployments across staging and production.
- Instituted a centralized logging and alerting system, reducing downtime due to model failures by 25%.
- Worked closely with DevOps and Security teams to implement robust IAM policies and compliance standards.
*Data Scientist & AI Engineer | ShopSmart Retail, San Francisco, CA*
January 2017 – February 2019
- Designed machine learning models for sales forecasting, improving forecast accuracy by 12%.
- Built lightweight containerized models integrated into the existing cloud infrastructure, expediting deployment.
- Contributed to dashboard development for real-time inventory monitoring, enhancing decision-making speed.
EDUCATION
**Bachelor of Science in Computer Science**
University of Illinois, Urbana-Champaign
Graduated: 2016
CERTIFICATIONS
- AWS Certified Machine Learning – Specialty (2023)
- Certified Kubernetes Administrator (CKA) (2024)
- TensorFlow Developer Certificate (2022)
PROJECTS
- **Unified Customer 360 ML Platform:** Developed a centralized platform utilizing Apache Airflow and Kubernetes to automate data ingestion, model training, and deployment, resulting in faster onboarding of new models and insights for retail marketing campaigns.
- **Real-Time Price Optimization:** Implemented a low-latency ML system on AWS Lambda and DynamoDB enabling dynamic pricing adjustments across multiple retail channels, increasing revenue by 8% month-over-month.
TOOLS & TECHNOLOGIES
- Cloud: AWS (SageMaker, Lambda, CloudWatch), Azure ML, GCP AI Platform
- CI/CD: Jenkins, GitLab CI, CircleCI
- Container & Orchestration: Docker, Kubernetes, Helm
- Data Engineering: Apache Spark, Kafka, Airflow, Prefect
- Monitoring & Logging: Prometheus, Grafana, ELK Stack, DataDog
- ML Frameworks: TensorFlow, PyTorch, Scikit-learn
- Version Control: Git, DVC
LANGUAGES
- English (Fluent)
- Spanish (Proficient)
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