AI ML Engineer

About Springer Nature Group

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Job Title –AI ML Engineer 

Location :   Pune, India        

About Us 
 

“Emerging Technology” works on building innovative solutions to provide a hassle-free environment to all our researchers. Along with researchers, we also help internal Springer Nature teams in integrating AI solutions in their product for an easy-going experience. Our task here is to understand the pain points of our customers 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 optimizing editorial processes, ensuring system scalability and reliability, improving data quality, enhancing user experience, and driving business insights. By staying updated on AI/ML trends, the AIML Engineer supports continuous improvement and innovation, contributing to Springer Nature’s mission of advancing research communication and academic excellence. 
 

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: 

• Get familiar with Springer Nature’s technology stack, including AI/ML frameworks and cloud platforms (AWS, Azure, or 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: 

• 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: 

• 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. 

•  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  

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. 

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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://careers.springernature.com/