Job Title: Machine Learning ( MLOps) & Data Engineer
Experience: 5 - 7 Years

Position Summary
We are seeking a highly skilled Senior Machine Learning & MLOps / Data Engineer with 57 years of enterprise experience to join our CIP project team. In this role, you will design, deploy, and scale enterprise data engineering pipelines, automate ML model lifecycles, and establish robust MLOps practices across up-to-date cloud environments.

Key Responsibilities
- Pipeline & Architecture Engineering: Design, build, and maintain large-scale distributed data engineering pipelines using Python, Spark, Databricks, and orchestration engines like Apache Airflow.
- MLOps & Model Lifecycle Management: Implement end-to-end MLOps solutions, including model lifecycle tracking, feature store integration, automated experimentation, and robust production deployment strategies.
- Infrastructure & CI/CD: Establish automated deployment pipelines (CI/CD) via Azure DevOps, GitHub Actions, or Jenkins. Containerize applications using Docker and Kubernetes.
- Cloud & Big Data Infrastructure:



Manage distributed data workloads using cloud platforms (AWS, Azure, or GCP) alongside technologies like Apache Spark, Kafka, or Flink.
- Software Engineering Standards: Enforce high code-quality standards through version control, automated testing, secure coding practices, design patterns, and peer code reviews.
- Governance & Security: Ensure all data and model infrastructure adheres to enterprise data governance, privacy, security, and compliance protocols.

Qualifications & Skill Requirements
Must-Have (Required):
- Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field.
- Experience: 5–7 years of hands-on experience in Machine Learning Engineering, MLOps, Data Engineering, or Software Engineering.
- Big Data Systems: Proven experience with distributed systems like Apache Spark, Kafka, Hadoop, or Flink.
- Data Pipelines: P

📌 Machine Learning (Pune)
🏢 ACL Digital
📍 Pune