Machine Learning Operations Engineer
hace 1 semana
We are seeking an experienced Machine Learning Operations (MLOps) Engineer to join our EA Loc Data & AI team. The team's mission is to support and accelerate the use of machine learning across EA by building robust, automated, and scalable ML systems.
Key Responsibilities:- Design, build, and manage ML pipelines, from data extraction and preparation to model training, evaluation, and deployment.
- Model hyperparameter optimization.
- Automate the ML pipeline using MLOps tools and practices and optimize it for scalability and performance.
- Monitor ML models in production, manage their lifecycle, and ensure their reliability and performance.
- Model version tracking & governance.
- Collaborate with data scientists, data engineers, and business teams to understand their needs, implement ML solutions, and drive the adoption of MLOps.
- Conduct complex data analysis and report on results.
- Keep abreast of the latest trends and advancements in MLOps and machine learning, and contribute to the continuous improvement of MLOps practices at EA.
- Mentor junior team members and foster a culture of learning and sharing within the team.
- Bachelor's or master's degree in Computer Science, Software Engineering, Statistics, Applied Mathematics, or a related field.
- Minimum of 2-3 years of experience in ML Engineering/ MLOps or similar roles.
- Extensive knowledge of machine learning algorithms and principles.
- Proficiency in programming frameworks commonly used in machine and deep learning as PyTorch, Jax or Keras.
- Proficiency in code in Python.
- Experience on deep learning training optimization libraries/techniques such as Deepspeed, LoRA, PEFT, etc.
- Experience with MLOps tools such as MLFlow, Kubeflow or Weights and Biases.
- Solid experience with MLOps practices and tools, such as CI/CD, IaC (Infrastructure-as-code) tools (like CloudFormation, Terraform), automated testing, model monitoring, and version control.
- Experience with cloud computing platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
- Strong ability to build partnerships and foster collaboration across teams.
- Proven track record of driving results and innovation in MLOps or machine learning.
- Interest in gaming is a big plus.
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