ML Engineer CV Example
Professional ml engineer CV example with recruiter-tested sections you can customise in minutes.
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All personal details and career history in this example are fictional. Customise this CV with your own real information before applying.
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Benjamin Carter
Machine Learning Engineer
7 years of experience deploying machine learning models into production environments and developing scalable MLOps pipelines.
Experience
Senior ML Engineer
Model Circuit, Full-time
2019-08-01 – Present
Zurich, Switzerland
Production ML systems — Kubernetes inference serving, drift detection with auto-retraining, and canary model deployment.
- Operationalized machine learning systems for large-scale production use
- Built feature pipelines and online inference endpoints in Kubernetes, serving sub-120ms recommendations at 4k RPS.
- Implemented drift detection using PSI and KS tests with automated retraining triggers, reducing stale-model incidents.
- Introduced canary deployment policies for model versions with shadow traffic evaluation before production cutover.
ML Engineer
Delta Intelligence, Full-time
2017-07-01 – 2019-07-01
Toronto, ON, CA
Training and serving infrastructure for ranking — distributed PyTorch training, MLflow model registry, and FAISS retrieval.
- Developed model training and serving infrastructure for ranking systems
- Containerized PyTorch training jobs with distributed data parallel execution, cutting training time from 11 to 6 hours.
- Created model registry workflows with approval gates and lineage metadata using MLflow and GitOps controls.
- Built low-latency ANN retrieval services with FAISS for semantic search over 40M product descriptions.
Junior ML Engineer
Prism Adaptive, Full-time
2015-06-01 – 2017-06-01
Amsterdam, Netherlands
ML platform reliability and integration — TFDV data contracts, Airflow batch inference, and reproducible environments.
- Supported ML platform reliability and model integration tasks
- Implemented data validation contracts with TensorFlow Data Validation to catch feature schema breaks early.
- Wrote batch inference orchestration jobs in Airflow with checkpoint recovery for long-running workloads.
- Added reproducible environment lockfiles for training jobs, eliminating dependency mismatch failures in CI.
Education
Computer Science, Bachelor of Science
Carnegie Mellon University
2015-09-01 – 2019-06-01
Bachelor's-level training in computer science at Carnegie Mellon University. Completed coursework in Python, PyTorch, TensorFlow, capstone projects, and collaborative assignments that prepared for professional roles.
Skills
Certifications
Google Professional Machine Learning Engineer
Google
2023-06-01
AWS Certified Machine Learning - Specialty
AWS
2022-06-01
Languages
English (Native)
CV writing guide
- Show both model quality improvements and production reliability metrics.
- Include examples of scalable serving, observability, and retraining automation.
- Demonstrate strong collaboration with data scientists and platform engineers.
- Google Professional Machine Learning Engineer
- AWS Certified Machine Learning - Specialty
- Databricks Certified Machine Learning Professional