Machine Learning Engineer

Job Title: Machine Learning Engineer
Location: Pune, India
Application Deadline: n/a

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

The highly-regarded Springer Nature's Data and Analytics Solutions group is responsible for harnessing data and developing innovative solutions that enhance the research community's experience, especially in the Research Intelligence domain. Contributing to the creation of new data products, the group supports Springer Nature's Research division, which includes Nature, Springer, BioMedCentral, and Scientific American via Nature Research Intelligence. Our collaborative and inclusive environment fosters innovation and growth through diversity, allowing individuals from different backgrounds and experiences to enhance our culture and achieve common goals.

About the Role

We’re seeking a talented Machine Learning Engineer to join the Nature Navigator team within Research Intelligence. You'll collaborate with data scientists, analysts, and engineers to develop and operationalize machine learning models and solutions, leveraging state-of-the-art technologies. This role is an opportunity to drive data science advancements and implement cutting-edge techniques including graph databases, GPT, TensorFlow, Google BigQuery, and Google Vertex AI. You'll be contributing to Springer Nature's vision of advancing discovery through impactful, scalable solutions.

Role Responsibilities:

As a Machine Learning Engineer, your key responsibilities will include:

• Building, deploying, and monitoring machine learning models and pipelines.

• Developing and implementing ML solutions with the broader team.

• Advocating for MLOps best practices, enhancing the adoption and standardization across the organization.

• Leading initiatives towards advanced analytics using statistical modeling, machine learning, and AI.

What you will be doing

Within 3 months you will:

• Familiarize yourself with the existing data and analytics technologies, including Google BigQuery, Vertex AI, neo4j and LangGraph.

• Build initial machine learning models and become part of the weekly sync-ups.
   

By 3-6 months you will:

• Collaborate in enhancing the machine learning infrastructure and supporting broader business integration.

• Deepen your understanding of the organization’s data sources, and contribute to models and product features for impactful decision-making.
   

By 6-12 months you will:

• Mentor new team members and contribute to recruitment efforts.

• Lead efforts to increase the use of predictive analytics and advocate for the adoption of advanced data techniques.

• Engage with various stakeholders to ensure alignment in ML solution implementation.

About You

• You have a University degree with a strong analytical/quantitative background or equivalent experience (e.g. Data Science, Statistics, Mathematics, Econometrics, Physics, Computer Science etc.)

• You hold strong statistical and machine learning skills with a desire to continually learn and apply new knowledge

• You demonstrate experience in using machine learning to add tangible value in achieving the wider goals and strategy of the business

• You have demonstrable experience in working with various stakeholders, such as data scientists, engineers or product managers

• You are familiar with scientific publishing data

• You possess a strong working knowledge of SQL, Python, and Git, along with solid experience in at least one cloud environment, such as GCP (preferred), AWS or Azure

• You are adept at data extraction, cleansing, and interpretation using tools like SQL, Big Query and Python

• You have Demonstrable experience deploying models and pipelines in a cloud environment, such as GCP

• You are familiar with embedding models, vector search systems and large language models, including prompt engineering

• You have past experience with Plotly Dash

• You communicate effectively in English, both written and spoken, and enjoy networking to build relationships across the company

• You are well-organized, with strong problem-solving skills and business acumen

For all roles in all locations, we offer a competitive, industry-benchmarked salary. To find out more about the package provided at each location, please visit sndigital.springernature.com.

Job Posting End Date: