11+ years of experience preferred.

Proven track record of designing and implementing large-scale ML pipelines and

infrastructure.

Experience with distributed computing frameworks (Spark, Hadoop)

Knowledge of graph databases and auto ML libraries

Bachelor's / Master’s degree in computer science, analytics, mathematics, statistics

Strong experience in Python, SQL.

Solid understanding and knowledge of containerization technologies (Docker,

Kubernetes).

Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms

(Kubeflow, MLFlow)

Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow,

PyTorch).

Certifications in cloud platforms or ML technologies can be a plus.

Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization

technologies (Docker, Kubernetes).

Strong problem-solving and analytical skills.

Ability to plan, execute and take ownership of task.