Senior Gen Ai Engineer

Role Overview: SciSpace is a leading platform for researchers worldwide to create, collaborate, and publish their research. The company offers solutions for scholarly content creation, publication, and dissemination needs. SciSpace has been featured in prominent publications like Forbes, Nasdaq, and Entrepreneur magazine. As a Senior Research Scientist at SciSpace, you will play a crucial role in developing Gen AI based ML systems and ensuring their deployment at scale to benefit researchers. Key Responsibilities: - Design, develop, and maintain scalable and efficient machine learning systems, including writing ML services and APIs. - Implement and manage the deployment of machine learning models, including transformer based LLMs, into production environments to ensure reliability and scalability. - Collaborate with infrastructure teams to optimize and manage systems supporting machine learning workflows. - Create robust and efficient data pipelines for collecting, processing, and preparing datasets for machine learning models. - Work closely with data scientists, researchers, and cross-functional teams to integrate ML solutions into existing software infrastructure. - Continuously optimize and improve the performance of machine learning algorithms and systems. - Develop and maintain documentation for machine learning systems, APIs, and data pipelines to ensure clarity and ease of use for team members. Qualifications Required: - 3+ years of experience including working on designing multi-component systems. - Strong grasp of one high-level language like Python. - General awareness of SQL and database design concepts. - Solid understanding of testing fundamentals. - Strong communication skills. - Prior experience in managing and executing technology products. - Decent understanding of various Gen AI based ML approaches. - Experience in building agentic architectures using langgraph or similar libraries. - Bonus: Prior experience working with high-volume, always-available web applications. - Knowledge of cloud platforms such as AWS, GCP, or Azure. - Experience with deploying small and big open source LLMs in production environments using containerization tools like Docker. - Experience in Distributed systems. - Experience working with startups is a plus point. Role Overview: SciSpace is a leading platform for researchers worldwide to create, collaborate, and publish their research. The company offers solutions for scholarly content creation, publication, and dissemination needs. SciSpace has been featured in prominent publications like Forbes, Nasdaq, and Entrepreneur magazine. As a Senior Research Scientist at SciSpace, you will play a crucial role in developing Gen AI based ML systems and ensuring their deployment at scale to benefit researchers. Key Responsibilities: - Design, develop, and maintain scalable and efficient machine learning systems, including writing ML services and APIs. - Implement and manage the deployment of machine learning models, including transformer based LLMs, into production environments to ensure reliability and scalability. - Collaborate with infrastructure teams to optimize and manage systems supporting machine learning workflows. - Create robust and efficient data pipelines for collecting, processing, and preparing datasets for machine learning models. - Work closely with data scientists, researchers, and cross-functional teams to integrate ML solutions into existing software infrastructure. - Continuously optimize and improve the performance of machine learning algorithms and systems. - Develop and maintain documentation for machine learning systems, APIs, and data pipelines to ensure clarity and ease of use for team members. Qualifications Required: - 3+ years of experience including working on designing multi-component systems. - Strong grasp of one high-level language like Python. - General awareness of SQL and database design concepts. - Solid understanding of testing fundamentals. - Strong communication skills. - Prior experience in managing and executing technology products. - Decent understanding of various Gen AI based ML approaches. - Experience in building agentic architectures using langgraph or similar libraries. - Bonus: Prior experience working with high-volume, always-available web applications. - Knowledge of cloud platforms such as AWS, GCP, or Azure. - Experience with deploying small and big open source LLMs in production environments using containerization tools like Docker. - Experience in Distributed systems. - Experience working with startups is a plus point.