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 175 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.
Required Qualifications
- 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.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Strong understanding of machine learning concepts and algorithms.
- Experience with software development practices and methodologies, including version control, testing, and deployment.
- Excellent problem-solving and analytical skills.
- Effective communication and teamwork skills.
- Experience in Generative AI, LLM, building RAG applications, model optimization. Hands on experience in NLP.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud for deploying AI/ML
Springer Nature Skills associated with this Job Profile include:
SN-Process Optimization, SN-Storytelling, SN-Big Data Management, SN-Data Security & Governance, SN-Software Engineering & Systems Integration , SN-Product Development & Delivery, SN-Process & Systems Design, SN-Communicates Effectively, SN-Tech Savvy, SN-Manages Complexity
At Springer Nature, our mission is to be part of progress – and that begins with inclusion: of people, perspectives, and ideas. We believe that diverse perspectives drive progress, and we are committed to creating an environment where people and ideas can flourish. If you have any access needs related to disability, neurodivergence or a chronic condition, please contact us so we can make all necessary accommodation. Find out more about our DEI work here https://group.springernature.com/gp/group/taking-responsibility/diversity-equity-inclusion
For more information about career opportunities in Springer Nature please visit https://springernature.wd3.myworkdayjobs.com/SpringerNatureCareers/
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Job Posting End Date:
14-07-2026Skills Required
- Bachelor's or master's degree in Computer Science, Engineering, or related field.
- 3+ years of experience in AI/ML engineering.
- Proficiency in Python and R.
- Experience with TensorFlow, PyTorch, or scikit-learn.
- Strong understanding of machine learning concepts and algorithms.
- Experience with software development practices: version control, testing, deployment.
- Excellent problem-solving and analytical skills.
- Effective communication and teamwork skills.
- Experience in Generative AI, LLMs, building RAG applications, model optimization; hands-on NLP experience.
- Knowledge of cloud platforms for deploying AI/ML (AWS, Azure, or Google Cloud).
What We Do
Research and learning are the cornerstones of progress, which is why we open doors to discovery for our communities, enabling millions of researchers, clinicians, educators and other professionals to access, trust and make sense of the latest insights. Springer Nature is an ambitious and dynamic organisation. For over 180 years our imprints, books, journals, platforms, and technology solutions have been a trusted source of knowledge to our communities. Today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood, and used, ensuring that the world continues to make progress, improving and enriching lives and helping to protect our planet for future generations. Global key facts: Established for over 180 years Nearly 10,000 colleagues 200 offices in 45 countries on all continents World’s largest academic book publisher Publisher of Nature, the world’s most influential journal First company to publish more than 1 million Open Access articles Key brands and imprints: Springer Nature is home to some of the best-known names in research, health, educational and professional publishing. Every day, around the globe, our brands reach millions of people. Nature Springer BMC Palgrave Macmillan Apress Macmillan Education Scientific American Springer Healthcare Springer Medizin Research Square J.B. Metzler BSL Adis
