3+ years relevant experience in Software
Good in Problem Solving & Data Structures
• Strong knowledge in Python programming & libraries like Pandas, NumPy, etc
• Experience with GCP/AWS/Azure Cloud, Docker/Kubernetes and scale containerized apps
• Experience in Apache Spark or PySpark, Kafka
• Good knowledge in SQL Queries and any RDBMS DB.
• Understanding of CI/CD tools like Jenkins & SonarQube
• Implement & deploy models into production by leveraging MLOps best practices.
• Strong communication skills in a collaborative environment
• Experience in Big data technologies such as Hadoop,
• Experience in MLFlow & DVC
• Experience in working on ETL Jobs and building pipelines using UC4/Airflow.
Job Responsibilities:
• Collaborate with Data Scientists, Data Engineers, cloud platform and application engineers to create and implement inferencing pipelines and governance for ML/DL model lifecycle
• Collaborate with Data science & other dependent teams to design and implement the required solutions
• Participate in formal and informal code reviews to ensure code quality
• Actively contribute to the automated test suites to enable continuous integration
