Job Title

Job Description- 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.