Applied AI/ML Lead

Be an integral part of a innovative and forward thinking agile team to enhance, build, and deliver advanced technology products.

As an Applied AI/ML Lead within the Corporate Sector, Trade Surveillance Technology team, you will be responsible for delivering AI/ML enabled analytical and technical solutions that support the market surveillance and regulatory compliance capabilities.

You will work across the full model lifecycle-from problem framing and data exploration to model development, productionization, and monitoring, partnering closely with data science and engineering teams.

You will translate ambiguous business needs into robust, production-grade AI systems while championing sound engineering and responsible AI practices.

This is a hands-on technical role with growing scope for technical leadership, mentorship of junior engineers, and influence over architectural decisions.

Job Responsibilities


* Model development: Design, train, evaluate, and fine-tune machine learning, deep learning, and large language models (LLMs) to address defined business use cases.


* Productionization (MLOps): Build and maintain scalable, reliable ML/Feature/Data pipelines for training, deployment, inference, and monitoring in production environments.


* Data engineering collaboration: Work with large, complex datasets-performing feature engineering, data validation, and preprocessing to ensure model quality and reproducibility.


* Applied research: Stay current with advances in AI/ML (e.g., generative AI, RAG, agentic frameworks) and prototype new techniques to evaluate their applicability.


* System integration: Integrate models and AI services into applications via APIs, ensuring performance, latency, and cost efficiency.


* Quality and governance: Implement testing, evaluation frameworks, and monitoring to detect drift, bias, and degradation; adhere to responsible AI and model risk standards.


* Cross-functional partnership: Collaborate with data scientists and software engineers to scope requirements and deliver end-to-end solutions.


* Documentation and mentorship: Produce clear technical documentation and provide guidance and code review support to junior team members.


* Lead projects end to end: Guide and lead projects from understanding and establishing requirements, to design and final implementation/testing/delivery

Required Qualifications, Capabilities, and Skills


* Master's degree in Computer Science, Machine Learning, Data Science, Engineering, Mathematics, or a related quantitative field (or equivalent practical experience) and 6+ years of hands-on experience building and deploying ML/AI models in production settings.


* Strong programming proficiency in Python/SQL/Relational Databases/Linux and familiarity with AI/ML frameworks such as scikit-learn, PyTorch, SmartSDK for Agent building, base libraries such as pandas, numpy, etc.


* Solid understanding of ML fundamentals: supervised/unsupervi...