Senior ML Engineer (AI)

External

Springernature · Pune, India

Full-timeOn-siteToday

CI/CDData AnalysisDocumentationFeature EngineeringGenerative AILLMs

Cover Letter Connect

Prepare for this interview

Elite

AI-generated questions, company research, and talking points tailored to this role

About the role

Springer Nature AI labs work on building innovative solutions to accelerate discovery and scientific progress for the research community. Along with researchers, we also help internal Springer Nature teams in integrating AI solutions in their products for a state-of-the-art experience. Our task here is to understand the pain points of our customers, develop problem statements together with them and come up with the most innovative, cost effective and scalable solution. Our team is responsible for staying up to date with the latest technology trends in the field of AI and GenAI. We conduct experiments to validate their implications and applications at Springer Nature. The purpose of the AIML Engineer role at Springer Nature is to enhance the publishing cycle using advanced AI and ML skills. This role focuses on improving operational efficiency and decision-making by developing and deploying AI/ML solutions to streamline processes, improve data accuracy, and enable new capabilities. Key responsibilities include staying updated on AI/ML trends, ensuring system scalability and reliability, improving data quality, detailed data analysis, enhancing user experience, and driving business insights.

Responsibilities

Design, develop, and deploy end-to-end AI/ML solutions, ensuring scalability, efficiency, and robustness.

Lead AI/ML initiatives, collaborating with cross-functional teams including data scientists, software engineers, and product managers.

Architect and optimize AI infrastructure, including data pipelines, model training workflows, and deployment systems.

Evaluate, benchmark, and fine-tune AI/ML models to ensure optimal performance in production environments.

Implement and enforce best practices for model monitoring, retraining, and maintenance.

Drive innovation by researching, prototyping, and implementing cutting-edge AI technologies, including Generative AI and Large Language Models (LLMs).

Provide technical mentorship and guidance to junior AI/ML engineers and contribute to their professional growth.

Collaborate with non-technical stakeholders to translate business challenges into AI/ML solutions and communicate results effectively.

Develop and contribute to AI governance frameworks, ensuring ethical and responsible AI practices.

Lead initiatives for integrating AI/ML models into existing and new Springer Nature platforms to enhance user experiences.

Within 3 Months:

Gain a deep understanding of Springer Nature's AI/ML ecosystem, including technology stack, data infrastructure, and cloud platforms (Google Cloud).

Take ownership of small-to-medium AI/ML projects, collaborating with team members to design, implement, and deploy models.

Participate in architecture discussions and contribute to technical design decisions for AI solutions.

Review existing models, identify potential optimizations, and propose improvements.

Establish best practices for model deployment, testing, and monitoring.

Work closely with data scientists to enhance feature engineering and improve model performance.

Contribute to documentation, knowledge sharing, and internal technical discussions.

By 3-6 Months:

Lead the design and development of AI/ML solutions, ensuring high scalability and performance.

Optimize AI/ML model inference and deployment pipelines to meet production requirements.

Implement monitoring and alerting mechanisms for deployed AI models to track performance degradation and ensure timely retraining.

Engage with business and product teams to identify AI-driven opportunities that enhance editorial workflows and customer experiences.

Conduct deep-dive research into new AI methodologies, including model compression, fine-tuning strategies, and RAG applications.

Mentor junior AI/ML engineers, providing technical guidance and conducting code reviews.

Drive improvements in AI infrastructure, including automation, CI/CD pipelines, and GPU resource management.

By 6-12 Months:

Own and drive multiple AI/ML projects from conception to deployment, ensuring alignment with business objectives.

Lead AI research initiatives, evaluating the latest advancements and integrating state-of-the-art techniques into production models.

Influence and shape the AI/ML roadmap, identifying opportunities for automation and

Senior ML Engineer (AI)

About the role

Responsibilities

Additional Information

Your Match

Company Intel

What employees say

Interested in this role?