Lead Developer

Overview:

Job Purpose

Intercontinental Exchange, Inc. (ICE) presents an opportunity for a full-time Lead Developer to join a team responsible for development of the platform for providing cutting edge AI and ML solutions across the enterprise. The Lead Developer will have experience in all phases of software development lifecycle, from requirements gathering, to design, coding, unit testing, debugging, and supporting in production.

The candidate will be part of a newly formed ICE AI Center of Excellence team, key to ICE’s long-term strategy to incorporate Gen AI technologies in our solutions in a responsible and sustainable way across the enterprise. The ideal candidate should be knowledgeable in designing and developing solutions using the modern advancements in Gen AI, database systems and scripting languages.

This position requires technical proficiency/problem solving as well as an eager attitude, professionalism, and solid communication skills. Strong written and oral communication is required as the applicant will frequently be interacting with the diverse teams across the enterprise to achieve business goals.

Responsibilities

On any day, the candidate could be doing any or all of the following:

• Analyze requirements and propose technical solutions in delivering projects within expected parameters of cost, time, and quality. Ensure solutions leverage advanced AI/ML techniques effectively.
• Design and implement experimental frameworks and innovative systems for data collection, ensuring integration with AI/ML pipelines and tools to automate data processing.
• Create comprehensive reports and presentations to communicate findings, model performance, and project progress to stakeholders, providing actionable insights.
• Utilize advanced statistical and machine learning tools to identify, analyze, and interpret patterns and trends in complex data sets to support diagnosis, prediction, and decision-making processes.
• Develop, optimize, and maintain robust databases and data systems, ensuring data integrity and accessibility in a readable format.
• Collaborate with project managers to compile detailed work breakdown structures, providing realistic estimates for task completion, and ensuring timely delivery of high-quality solutions.
• Develop and conduct unit tests for all new or modified functions, adhering to best practices in software development and ensuring high code quality and reliability.
• Collaborate closely with other Developers and QA Engineers to execute full-cycle integration, functional, and regression testing, ensuring seamless deployment and operation of AI/ML solutions.
• Continuously monitor and improve system performance, proposing and implementing enhancements to achieve better efficiency and effectiveness.
• Engage effectively with business and operations teams to address and resolve design and operational challenges, ensuring AI/ML solutions meet business needs.
• Lead brainstorming sessions to identify innovative ML/AI/NLP applications for broad spectrum of applications across the enterprise, driving advancements in automation, knowledge discovery, and insight generation.
• Implement and prototype new algorithms, with a strong focus on writing efficient and scalable code for novel ML/AI/NLP solutions.
• Mentor and guide junior team members, sharing expertise in AI/ML development to foster a culture of continuous learning and improvement within the team.

Knowledge and Experience

• Advanced degree (PhD preferred, MS with significant experience) in a quantitative field such as Computer Science, Electrical Engineering, Information Sciences, Statistics, Mathematics, Economics, Operations Research, or a related field with a focus on AI/ML and statistical analysis.
• Strong, proven programming skills in Python and one or more of C, C++, Java or C#. Experience in CUDA development for high-performance computing tasks is highly desirable.
• Extensive experience with AI/ML libraries and tools (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, SciPy), including their application in developing and deploying machine learning models.
• Proficiency in SQL and experience with database management and data manipulation, ensuring efficient data storage, retrieval, and processing.
• Experience with big data technologies such as Spark and Hadoop, and familiarity with data formats like PARQUET, ensuring scalable data processing capabilities.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud, including data services like AWS S3, Redshift, Azure Data Lake, or Google BigQuery, ensuring robust and scalable cloud-based solutions.
• Familiarity with data engineering concepts and tools (e.g., Apache Airflow, Kafka) to support data pipeline development and management.
• Solid understanding of version control tools (ideally Git) and collaborative coding practices to ensure efficient and reliable codebase management.
• Experience in applying AI/ML-driven statistical analysis and modeling solutions to real-world problems, preferably in a financial context, demonstrating practical and impactful implementations.
• Experience with deploying machine learning models into production environments, ensuring their scalability, reliability, and performance in real-world applications.
• Knowledge of continuous integration and continuous deployment (CI/CD) pipelines for AI/ML projects to streamline development and deployment processes.
• Excellent communication skills (oral and written) to explain complex algorithms and solutions to stakeholders across multiple disciplines and to work effectively in a diverse team environment.
• Desirable to possess experience in an applied R&D environment, working in an agile and innovation-lab culture, fostering continuous learning, experimentation, and improvement.

Schedule

This role offers work from home flexibility of one day per week.

Intercontinental Exchange, Inc. is an Equal Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin or ancestry, age, disability or veteran status, or other protected status.