Drive the vision for modern data and analytics platform to deliver well architected and engineered data and analytics products leveraging cloud tech stack and third-party products
Close the gap between ML research and production to create ground-breaking new products, features and solve problems for our customers
Design, develop, test, and deploy data pipelines, machine learning infrastructure and client-facing products and services
Build and implement machine learning models and prototype solutions for proof-of-concept
Scale existing ML models into production on a variety of cloud platforms
Analyze and resolve architectural problems, working closely with engineering, data science and operations teams
Preferred candidate profile
Minimum Qualifications / Skills
Bachelor's degree in computer science engineering, information technology or BSc in Computer Science, Mathematics or similar field
Masters degree is a plus
Integration APIs, micro-services and ETL/ELT patterns
DevOps (Good to have) Ansible, Jenkins, ELK
Containerization Docker, Kubernetes etc
Orchestration Airflow, Step Functions, Ctrl M etc
Languages and scripting: Python, Scala Java etc
Cloud Services - AWS, GCP, Azure and Cloud Native
Analytics and ML tooling Sagemaker, ML Studio
Execution Paradigm low latency/Streaming, batch
Preferred Qualifications/ Skills
Data platforms Big Data (Hadoop, Spark, Hive, Kafka etc.) and Data Warehouse (Teradata, Redshift, BigQuery, Snowflake etc.)
Visualization Tools - PowerBI, Tableau
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full time