The prospect

As an ML Engineer, you will be responsible for the deployment of our core data science and AI models into our Global Mobility Solution platform.
- On this position you will:
- Contribute to the building of our ML Operations platform
- Support model deployment into Production platforms, ensuring effective model management (artifact versioning, serving, inference pipelines, production integration)
- Support monitoring, logging, and observability to ensure system reliability and performance.
- Build and manage containerized deployment environments.
- Evaluate and integrate cloud-native services, distributed computing frameworks, and infrastructure automation tools.
- Collaborate with data scientists, cloud engineers and data engineers to support, troubleshoot, and optimize AI models productionalization.
- Transform proof-of-concept models into production-ready solutions and deploy them at scale
- Build model performance benchmarking, evaluation and monitoring capabilities.
- To join our team,you will need:
- Education:
Bachelor degree in Computer Science,





Master preferred
- Languages:
You are fluent in English.
- Experience:
- 3-4 years of experience in deploying, monitoring and maintaining machine learning models in cloud environments
- Skills & Qualifications:
Demonstrated experience with:
- Cloud platform technology (AWS, Terraform, Kubernetes,...)
- Linux-based systems, containerization, and workflow orchestration (Linux, Bash, Docker, Airflow,...)
- Data storage, ingestion, and processing technologies (SQL, NoSQL, data lakes, object storage, batch and streaming pipelines)
- Software engineering tools and practices (Python, Git, Unit testing, CI/CD principles)
- Deployment of production-level software
- Machine Learning lifecycle (MLOps)
- Strong understanding of software development lifecycle and best practices.

Good problem-solving skills and attention to detail.

Must be able to function independently as well as work in a collaborative team en

📌 Associate Machine Learning Engineer (Hyderabad)
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📍 Hyderabad