Machine Learning Engineer

Machine Learning Engineer – Contract (12 Months)

Location: Remote (India)

Contract Length: 12 months

We are looking for an experienced Machine Learning Engineer to join a global data and analytics programme, supporting the development of predictive automation solutions using large-scale commercial datasets. This role focuses on building, deploying, and optimising machine learning models on an enterprise data platform, with a strong emphasis

on PySpark and distributed data processing.

This is a hands-on engineering role suited to someone who enjoys working with complex, multi-source data and translating advanced analytics into real-world commercial impact.

What you’ll be doing:

- Designing and implementing machine learning and deep learning models using PySpark on an enterprise data platform. - Solving complex analytical problems using large, distributed commercial datasets. - Building and maintaining end-to-end ML pipelines, from data ingestion through to deployment and monitoring. - Collaborating closely with commercial, analytics, and data engineering stakeholders to align technical solutions with business goals. - Identifying data drift, bias, and performance issues, and ensuring models generalise effectively in production. - Delivering actionable outputs such as segmentation, targeting, and optimisation recommendations. - Keeping up to date with advances in machine learning, big data, and automation technologies.

Key responsibilities:

- Ingesting, cleaning, and transforming large-scale datasets using PySpark. - Developing, evaluating, documenting, and monitoring ML models in a production environment. - Designing and optimising ETL and data pipelines to support scalable ML operations. - Working with stakeholders to define requirements and translate business objectives into technical solutions. - Customising or extending ML libraries (e.g. PySpark MLlib)to maximise analytical value.

Skills & experience required:

- Strong experience working with large-scale, distributed data sets. - Advanced knowledge of statistics, probability, algorithms, and machine learning concepts. - Hands-on experience with PySpark and big data processing. - Strong Python development skills. - Experience with enterprise data platforms and data modelling. - Excellent communication and collaboration skills. - Proactive mindset with a willingness to learn new tool sand technologies.

Desirable experience:

- Background in machine learning within pharmaceutical, life sciences, or commercial analytics environments. - Practical experience deploying ML solutions on enterprise data platforms. - Exposure to additional ML frameworks such as PyTorch or Keras (nice to have). - Bachelor’s or higher degree in computer science, mathematics, engineering, or a related quantitative field.