Senior Platform Engineer

Role Overview :

As a Senior Platform Engineer, you will be instrumental in designing, developing, and maintaining the core platform that powers our Generative AI applications. You will collaborate closely with data scientists, machine learning engineers, and product managers to build scalable, reliable, and efficient infrastructure for training, deploying, and monitoring LLMs. Your work will directly impact the performance and availability of our AI-driven products, ensuring a seamless and impactful user experience for millions.

Key Responsibilities :

- Design and implement robust and scalable infrastructure for training, deploying, and monitoring large language models (LLMs) to support our Generative AI initiatives.

- Develop and maintain Python-based APIs and services that facilitate seamless integration between various platform components, ensuring efficient data flow and processing.

- Optimize platform performance by identifying and addressing bottlenecks in the data pipeline, model serving infrastructure, and resource utilization, leading to improved efficiency and cost savings.

- Collaborate with data scientists and machine learning engineers to understand their infrastructure requirements and translate them into scalable and reliable platform solutions, enabling faster model development and deployment cycles.

- Implement monitoring and alerting systems to proactively identify and resolve platform issues, ensuring high availability and reliability of our AI-powered services for our users.

- Contribute to the development of best practices for platform engineering, including infrastructure-as-code, continuous integration/continuous deployment (CI/CD), and automated testing, promoting a culture of quality and efficiency.

Required Skillset :

- Demonstrated ability to design, develop, and maintain scalable and reliable platforms using Python.

- Proven experience in building and deploying applications using cloud platforms such as AWS, Azure, or GCP.

- Strong understanding of machine learning infrastructure and experience with tools and frameworks for training, deploying, and monitoring LLMs.

- Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences.

- Bachelor's or Master's degree in Computer Science or a related field.

- Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities.