Applied AI & Machine Learning Engineer

Job No.: BRQ-APAC-HYD-AIML-021
Location: Hyderabad, India
Region: Bruqe APAC
Team: Applied AI & Modelling
Level: Engineer
Employment Type: Full Time
Reporting To: Technical Lead, APAC

The Role

Bruqe is seeking an Applied AI & Machine Learning Engineer to develop the technical foundations of its decision-intelligence capability.

You will build and improve models, data pipelines, and analytical components that turn complex market, industry, technology, and operational data into reliable decision tools. The role requires strong engineering discipline alongside an interest in applying machine learning to consequential strategic questions—not technology experimentation in isolation.

What You Will Do

• Design, build, and maintain machine-learning models and data-processing pipelines for decision-intelligence applications.

• Integrate structured and unstructured data from market, company, technology, economic, policy, and operational sources.

• Develop methods for classification, forecasting, signal detection, natural-language processing, and pattern identification where appropriate.

• Evaluate model quality, robustness, explainability, and relevance to the decision context.

• Collaborate with data scientists, researchers, and advisory teams to translate strategic questions into technically rigorous solutions.

• Support the deployment of analytical components into Bruqe’s dashboards, system-mapping tools, and internal research workflows.

• Contribute to engineering standards covering code quality, documentation, reproducibility, version control, and responsible model use.

What You Will Bring

• An undergraduate or postgraduate degree in computer science, machine learning, data science, engineering, mathematics, or a related technical discipline.

• Experience building and deploying machine-learning, data-engineering, or analytical software solutions in a commercial, research, or consulting environment.

• Strong proficiency in Python and experience with relevant data and machine-learning libraries.

• Familiarity with SQL, APIs, data pipelines, cloud infrastructure, version control, and production-oriented software-development practices.

• Practical understanding of model evaluation, feature engineering, data quality, and the limitations of machine-learning methods.

• The ability to communicate technical concepts clearly and work effectively with non-technical colleagues.

• A disciplined, curious approach to solving complex problems where the underlying data and context may be incomplete or evolving.

What Success Looks Like

You will develop robust technical capabilities that improve the speed, quality, and depth of Bruqe’s analysis. Your work will help transform complex information into models and tools that are reliable, interpretable, and genuinely useful to teams and clients making high-stakes decisions.