AI/ML Engineer

ML Engineer:

• Strong experience of at-least 2-3 years in Python.
• 2 + years’ experience of working on feature/data pipelines and feature stores using Py-Spark.
• Exposure to AWS cloud services such as Sagemaker, Bedrock, Kendra etc.
• Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practice.
• Knowledge on Docker and Kubernetes.
• Experience with orchestration/scheduling tools like Argo.
• Experience building and consuming data from REST APIs.
• Demonstrable ability to think outside of the box and not be dependent on readily available tools.
• Excellent communication, presentation and interpersonal skills are a must.

Py-Spark AWS Engineer:

• Good hands-on experience of python and Bash Scripts.
• 4+ years of good hands-on exposure with Big Data technologies – Pyspark (Data frame and Spark SQL), Hadoop, and Hive
• Hands-on experience with using Cloud Platform provided Big Data technologies (i.e. Glue, EMR, RedShift, S3, Kinesis)
• Ability to write Glue jobs and utilise the different core functionalities of Glue.
• Good understanding of SQL and data warehouse tools like (Redshift).
• Experience with orchestration/scheduling tools like Airflow.
• Strong analytical, problem-solving, data analysis and research skills.
• Demonstrable ability to think outside of the box and not be dependent on readily available tools.
• Excellent communication, presentation and interpersonal skills are a must.

Roles & Responsibilities-

• Collaborate with data engineers & architects to implement and deploy scalable solutions.
• Provide technical guidance and code review of the deliverables.
• Play active role in estimation and planning.
• Communicate results to diverse technical and non-technical audiences.
• Generate actionable insights for business improvements.
• Ability to understand business requirements.
• Use case derivation and solution creation from structured/unstructured data.
• Actively drive a culture of knowledge-building and sharing within the team
• Encourage continuous innovation and out-of-the-box thinking.

Good To Have:

ML Engineer:

• Experience researching and applying large language and Generative AI models.
• Experience with Langchain, LLAMA Index, and Performance Evaluation frameworks.
• Experience working with model registry, model deployment & monitoring tools.
• ML-Flow / App. Monitoring tools.

Py-Spark AWS Engineer:

• Experience in migrating workload from on-premises to cloud and cloud to cloud migrations.
• Experience with Data quality frameworks.