Job Description
Company Overview: Our client, a leading global financial institution, operates in over 160 countries with approximately 200 million customer accounts. The company offers a comprehensive range of financial products and services, including consumer and corporate banking, investment banking, securities brokerage, and wealth management. With a commitment to innovation, security, and reliability, the company's Enterprise Operations & Technology division plays a critical role in ensuring seamless digital experiences, safeguarding financial assets, and optimizing operational efficiency. The organization values diversity, professional growth, and a culture of respect, fostering an inclusive environment where top talent can thrive. Role Overview: As a Principal AI/ML Engineer, you will be a key contributor to the Data Concerns Remediation Management platform, responsible for designing, prototyping, and developing core components. You will act as a trusted advisor to senior management and lead architects, ensuring high technical standards and best practices in software development and architecture. Key Responsibilities: Design and develop high-quality, reliable software solutions. Collaborate with development teams, quantitative analysts, and business experts. Ensure compliance with the company's security and Software Development Life Cycle (SDLC) standards. Manage and optimize large-scale platforms while continuously driving innovation. Required Skills & Qualifications: Technical Skills: Expertise in Python, Java, SQL, JavaScript (D3.js), Bash. Strong knowledge of AI/ML, particularly Large Language Models (LLMs) and Machine Learning techniques (Neural Networks, Decision Trees, SVM, NLP, Reinforcement Learning, Ensemble Methods Experience with Retrieval-Augmented Generation (RAG) and prompt engineering. Proficiency in advanced statistical and machine learning techniques. Hands-on experience with big data processing tools: Hadoop, Spark, Kafka, Hive, NumPy, Pandas, Matplotlib. Familiarity with CI/CD and MLOps frameworks such as MLflow and Weights & Biases. Experience in building and managing large-scale distributed systems. Strong system architecture and RESTful API design skills. Hands-on experience with Kubernetes and cloud-based development on at least one major public cloud provider. Familiarity with functional programming languages like Scala, Clojure, Rust, or Elixir. Professional Qualifications: Minimum 10+ years of relevant experience in software development and AI/ML engineering. Proven experience in project implementation, systems analysis, and software development. Recognized Subject Matter Expert (SME) in application development. Deep understanding of core business functions within financial services. Demonstrated leadership, project management, and stakeholder engagement skills. Education Requirements: Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience Master's degree preferred.