Lead MLOps Engineer

Mandatory skills

3+ years of experience in MLOps, Kubeflow, DevOps, or related fields.

Strong programming skills in Python, GoLang with experience in other languages such as Java, C++, or Scala being a plus.

Experience with ML frameworks such as TensorFlow, PyTorch, and/or scikit-learn.

Proficiency with CI/CD tools such as Github Actions.

Hands-on experience with AWS.

Familiarity with containerization and orchestration tools like Docker and Kubernetes.

Knowledge of infrastructure-as-code tools such as AWS CDK and Cloudformation.

Strong understanding of machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.

Excellent problem-solving skills and the ability to work independently as well as part of a team.

Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications: -

AWS Certified Machine Learning Specialty

Experience with feature stores, model registries, and monitoring tools such as MLflow, Tecton, or Seldon.

Familiarity with data engineering tools such as AWS EMR, Glue and Apache Spark.

Knowledge of security best practices for machine learning systems.

Experience with A/B testing and model performance monitoring

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