PhD Fellowship in Artificial Intelligence

Company Description Green Rock is a next-generation quantitative hedge fund operating at the intersection of finance, advanced artificial intelligence, and large-scale data engineering.

The firm focuses on treating global markets as evolving data problems, leveraging deep learning and massive alternative data to generate uncorrelated alpha in diverse market conditions.

Its “Lab-to-Live” ecosystem rapidly transforms complex AI models from research concepts into production-grade trading strategies, supported by a proprietary low-latency execution stack.

Green

Rock’s data-first architecture ingests and structures terabytes of unstructured alternative data, while AI-native prediction models dynamically adapt to shifting market regimes.

Led by entrepreneurial, data-driven AI technologists with deep expertise in data science and distributed systems, the firm maintains an agile, compliant, and technology-forward culture.

Role Description This is a full-time, on-site AI Software Engineer role based in Islamabad.

The AI Software Engineer will design, implement, and optimize machine learning and deep learning models that power autonomous trading strategies, with a focus on pattern recognition and neural network architectures.

Responsibilities include building production-grade software systems, integrating AI models into the proprietary trading stack, and collaborating with data scientists to transform research prototypes into scalable, reliable applications.

The role involves working with large, complex datasets, including alternative and unstructured data, and applying methods such as natural language processing to extract actionable signals.

The AI Software Engineer will also contribute to performance tuning, code reviews, and continuous improvement of model deployment, monitoring, and risk-management tools.

Qualifications

• Strong foundation in Computer Science, including algorithms, data structures, and software engineering principles.

• Hands-on experience with Neural Networks and Pattern Recognition, ideally in quantitative finance or large-scale predictive modeling.

• Practical knowledge of Natural Language Processing (NLP), including working with unstructured text and sentiment or signal extraction.

• Proficiency in Software Development using modern programming languages (e.g., Python, C++, or Java) and experience with production-grade systems.

• Experience with machine learning frameworks (e.g., PyTorch, TensorFlow) and data processing tools (e.g., Pandas, Spark).

• Familiarity with distributed systems, high-performance computing, or low-latency architectures is highly beneficial.

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related quantitative field.

• Ability to work collaboratively in a multidisciplinary team, communicate complex technical concepts clearly, and take ownership of end-to-end solutions.