AI/ML Engineer

Primary skills needed - AI & ML Ops

Secondary - Infra Ops

Tertiary - AWS/Azure

Experience and Skills

- Experience: 7+ years in data engineering, 3+ years as an MLOps engineer.

- MLOps Pipelines: Design, develop, and implement using tools like MLflow and Apache Airflow.

- Cloud Experience: Working experience with AWS and Databricks.

- Technical Proficiency: Strong in Python, PySpark, SQL, machine learning, NLP, deep learning, and AWS services (SageMaker, BedRock, EC2, Lambda, S3, Glue Tables).

- Configuration Management: Experience with Ansible, Terraform, and building CI/CD pipelines.

Responsibilities

- Automate ML Lifecycle: From data ingestion to deployment and monitoring.

- Collaborate with Data Scientists: Understand data science lifecycle, translate needs into production-ready solutions.

- Model Deployment and Monitoring: Strong in ML model deployment, AI ML pipeline, and model monitoring.

- Communication: Excellent written and verbal communication skills.

Desired Qualities

- Analytical Mindset: Ability to interpret data and metrics.

- Collaboration: Technical proficiency and ability to work with technical teams.

- ML Techniques: Familiarity with algorithms like RNN, CNN, GNN, GAN.