Advanced Engineer - AI/ML with Devops(GCP,AWS)
On-siteBengaluru, Karnataka, India
Job Summary
Design, develop, train, and deploy Machine Learning and AI models for real-world applications, building end-to-end ML pipelines including data preprocessing, training, validation, and monitoring. Develop Python-based automation for test suites and workflow orchestration, integrating ML pipelines seamlessly into CI/CD pipelines for continuous testing and deployment. Ensure a smooth build environment using CMake and Bazel, collaborate with DevOps teams to enable MLOps best practices, and deploy, monitor, and optimize ML workloads in AWS environments. Troubleshoot and resolve build, deployment, and performance issues across environments. Requires 6 to 9 years of hands-on experience in AI/ML development with strong proficiency in Python, Git, and AWS cloud services.
Required Qualifications
- 6 to 9 years of hands-on experience in AI / Machine Learning development
- Strong proficiency in Python, especially for automation, ML model development, and testing
- Extensive hands-on experience in automating test suites and processes using Python
- Solid experience integrating ML and automation workflows into CI/CD pipelines
- Hands-on experience with version control systems such as Git, GitLab, and GitHub
- Strong understanding of DevOps practices, including build, release, and deployment automation
- Experience working with AWS cloud services for ML model deployment and infrastructure
- Practical experience with CMake and Bazel for managing and maintaining stable build environments
- Good problem-solving skills with a strong attention to detail
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related fields
- Strong understanding of ML fundamentals, algorithms, and model lifecycle management
- Excellent communication and collaboration skills
- Ability to work independently while contributing effectively to cross-functional teams
- You are expected to work all 5 days in a week in office
Desired Qualifications
- Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow, etc.)
- Exposure to containerization and orchestration technologies like Docker and Kubernetes
- Experience with data processing frameworks (Pandas, NumPy, Spark, etc.)
- Knowledge of REST APIs / microservices for ML model serving
- Familiarity with monitoring and logging tools in cloud environments
- Prior experience in agile / scrum development teams
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