E
Junior Machine Learning Engineer
Not specifiedFull-timeAI & Machine LearningData InfrastructureEnterprise Software
Join an innovation-focused engineering team building data-driven solutions and production machine learning systems. The role focuses on MLOps, model deployment, monitoring, optimization, and collaboration with data scientists across the model lifecycle.
Responsibilities
- Transition machine learning models from research into production environments.
- Build and maintain automated CI/CD pipelines for model training, testing, and deployment.
- Develop MLOps tools for model-performance monitoring, drift detection, and alerting.
- Optimize production model latency and throughput.
- Partner with data scientists throughout the model lifecycle, from requirements and data analysis through production monitoring.
- Perform data analysis and ad hoc investigations to troubleshoot production issues, investigate model drift, and validate new data sources.
- Write maintainable, high-quality code and automate operational processes.
Requirements
- A degree in a relevant technological field.
- 1–2 years of experience in DevOps or machine learning engineering.
- Experience moving machine learning models from research or notebook environments into production.
- Advanced Python proficiency, including object-oriented programming and software engineering principles.
- Required experience with MLOps.
- Proficiency with Linux and shell scripting.
- Hands-on experience with Docker and familiarity with Kubernetes or OpenShift.
- Experience with CI/CD processes and tools such as Jenkins or Git/Bitbucket.
- Strong SQL, database, and ETL experience.
- Experience with monitoring and logging tools such as Splunk, Prometheus, or Grafana.
- Practical experience with machine learning libraries such as PyTorch, Pandas, NumPy, or scikit-learn.
- Ability to work independently, own tasks end to end, and collaborate effectively across engineering, data, and research teams.
Nice to have
- Experience with Dataiku.
- Experience developing and using APIs with FastAPI, Flask, or Django.
- Hands-on experience operating generative AI or large language model systems.