About Springer Nature Group

Springer Nature opens the doors to discovery for researchers, educators, clinicians, and other professionals. Every day, around the globe, our imprints, books, journals, platforms, and technology solutions reach millions of people. For over 181 years our brands and imprints have been a trusted source of knowledge to these communities and today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood, and used by our communities – enabling them to improve outcomes, make progress, and benefit the generations that follow.

About Us

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.

About the Role

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.

Key Responsibilities

• Develop end-to-end AI/ML solutions, from data collection and preprocessing to model development, deployment, and maintenance.
• Collaborate with data scientists to preprocess data and create features for model training.
• Implement and maintain AI infrastructure, including data pipelines and model deployment systems.
• Evaluate and compare different AI/ML models to select the most appropriate ones for specific tasks.
• Develop and deploy machine learning models.
• Optimize model performance and scalability for production environments.
• Research and experiment with new AI technologies to drive innovation.
• Communicate findings and insights to non-technical stakeholders through data visualization and storytelling.
• Apply machine learning, deep learning, Gen AI techniques to solve complex problems in areas such as natural language processing, computer vision, and predictive analytics.
• Monitor and maintain deployed models, including retraining and updating them as needed.

Within 3 Months:

Onboarding time, learning that things exist and working on simple tasks/tickets.

• Get familiar with Springer Nature's technology stack, including AI/ML frameworks and cloud platforms (Google Cloud).
• Begin developing and deploying AI/ML models under the guidance of senior team members.
• Participate in team agile processes and ceremonies, including daily stand-ups, planning, and retrospectives.
• Collaborate with data scientists to preprocess data and create features for model training.
• Share insights and opinions on building scalable and reliable AI/ML solutions.

By 3-6 Months:

Getting used to things, overview of the projects, and start working on it independently

• Become an active contributor to AI/ML solution development, focusing on optimizing model performance and scalability for production environments.
• Help improve AI infrastructure, including data pipelines and model deployment systems.
• Develop a solid understanding of Springer Nature's editorial processes and how AI/ML solutions can enhance operational efficiency.
• Engage in technical discussions with the team to improve product architecture and code quality.
• Communicate findings and insights to non-technical stakeholders through data visualization and storytelling.

By 6-12 Months:

Add value to products using the tools

• Lead the development and deployment of machine learning models and ensure their ongoing performance and scalability.
• Research and experiment with new AI technologies to drive innovation within the team.
• Onboard new team members and support their integration into the team’s agile processes.
• Participate in blameless post-mortems to identify and implement improvements.
• Proactively provide feedback and coaching to junior members of the team.
• Advocate for defining and implementing non-functional requirements and influence the design of the system architecture.
• Engage in user research to better understand the needs of researchers and other users of Springer Nature’s platforms.

About You

• Bachelor's or master's degree in computer science, Engineering, or related field.
• 3+ years of experience in AI/ML engineering, with a strong understanding of machine learning algorithms and deep learning frameworks
• Proficiency in programming languages such as Python, R and Data structures, Algorithms.
• Strong understanding of machine learning concepts and algorithms.
• Experience with software engineering practices and methodologies, including version control, testing, and deployment.
• Excellent problem-solving and data analytical skills.
• Effective communication and teamwork skills.
• Experience in Generative AI, LLM, building RAG applications, model optimization. Hands on experience in NLP or Computer Vision.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud for deploying AI/ML

Having a good command of English is important; collaboration is important in our day to day work, so being able to communicate your ideas and understand others’ is key.For all roles in all locations, we offer a competitive, industry-benchmarked salary.

Eligibility

In accordance with our internal career movement guidance, 12 months in current role is a requirement before applying to a new role

What we offer

The global setup of the team and the organization, our complex system and environment and its variety are giving a chance to further develop yourself while working with team members around the globe, and international stakeholders.

At Springer Nature, we value the diversity of our teams and work to build an inclusive culture, where people are treated fairly and can bring their differences to work and thrive. We empower our colleagues and value their diverse perspectives as we strive to attract, nurture and develop the very best talent. Springer Nature was awarded Diversity Team of the Year at the 2022 British Diversity Awards. Find out more about our DEI work here https://group.springernature.com/gp/group/taking-responsibility/diversity-equity-inclusion If you have any access needs related to disability, neurodivergence or a chronic condition, please contact us so we can make all necessary accommodation. For more information about career opportunities in Springer Nature please visit https://springernature.wd3.myworkdayjobs.com/SpringerNatureCareers

#LI-HD1