The Senior Engineer will develop AI infrastructure, implement MLOps, deploy models, write production code, and collaborate across teams while optimizing system performance.
Key Responsibilities
- Build AI Infrastructure: Contribute to the development and maintenance of scalable, reliable, and efficient infrastructure for training and deploying machine learning models.
- MLOps & Automation: Implement and maintain CI/CD pipelines for machine learning models, helping to automate the entire lifecycle from data preparation to model monitoring.
- Production Deployment: Deploy and maintain machine learning models in our production environments, ensuring high availability, low latency, and scalability.
- Software Development: Write clean, high-quality, and production-ready code to support AI/ML initiatives.
- Cross-Functional Collaboration: Partner with data scientists, other engineers, and product managers to understand model requirements and translate them into robust engineering solutions.
- Performance Optimization: Help monitor and optimize the performance of our AI systems, including model inference speed, resource utilization, and cost-effectiveness.
- Technology & Tooling: Work with modern tools, frameworks, and technologies in our AI engineering stack and stay current with the latest advancements in the field.
- Code Quality & Best Practices: Maintain and adhere to high standards for code quality, testing, and documentation.
- Educational Background: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
- Professional Experience: 3+ years of professional software engineering experience, with at least 1-2 years focused on AI/ML engineering, MLOps, or a similar backend role.
- Software Engineering Excellence: Strong proficiency in a major programming language (e.g., Python, Java, Go) and a solid foundation in software architecture, data structures, and algorithms.
- MLOps Knowledge: Hands-on experience building or maintaining MLOps pipelines using tools like Kubernetes, Docker, Jenkins, MLflow, Kubeflow, or similar technologies.
- Cloud Proficiency: Experience with at least one major cloud platform (AWS, GCP, or Azure) and its core services. Familiarity with its AI/ML services is a plus.
- Problem-Solving: Strong analytical and problem-solving skills, with the ability to troubleshoot technical issues.
- Experience with large-scale data processing technologies (e.g., Apache Spark, Kafka).
- Familiarity with infrastructure as code (IaC) tools like Terraform or CloudFormation.
- Experience optimizing deep learning models for inference (e.g., using TensorRT, ONNX).
- A passion for building and shipping products with AI at their core.
IKS Health Navi Mumbai, Maharashtra, IND Office
Raheja Mindspace, Airoli, Thane, Navi Mumbai, Maharashtra, India, 400708
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