Job Description

Company Insight:

A global leader in Systematic Equities and FICC is seeking to expand his close-knit, dynamic team of Research Engineers within the firms' cutting-edge data and AI infrastructure team. This team plays a crucial role in scaling state-of-the-art solutions that power the firm’s research-driven strategies. The team operates with petabyte-scale data and over a million CPU cores, making it one of the most technically advanced in the financial sector. Working closely with researchers, analysts, and traders, you'll design and develop high-performance infrastructure that directly influences live trading systems and provides critical insights. This is an exceptional opportunity to push the boundaries of data engineering and machine learning within the most innovative team in the industry.

Your Role:

In this role, you will:

• Design, develop, and deploy high-performance solutions to modernize AI and Alpha infrastructure
• Collaborate with researchers to define priorities, optimize pipelines, and enhance the efficiency of data workflows
• Work with massive datasets, including structured and unstructured data sources, to build scalable and impactful systems
• Stay on the cutting edge of open-source engineering and AI solutions, implementing them internally to maximize efficiency
• Build high-performance data pipelines and work directly with AI/ML models to push forward novel research
• Ensure data integrity, automate data pipelines, and streamline processes for end-users (researchers, quantitative analysts, and traders)

Experience Required / About You:

• At least 5 years of experience in data engineering, research engineering, or a related technical role
• Expertise in Python and C++, with a strong background in algorithmic development and data structures
• Experience with machine learning libraries/frameworks (e.g., PyTorch, HuggingFace ), as well as practical experience in handling large-scale datasets
• A demonstrated ability to build and optimize high-performance infrastructure
• Solid understanding of data engineering best practices, including data pipelines, ETL processes, and cloud technologies
• Strong communication skills to collaborate effectively with research teams and translate technical concepts into actionable insights

Preferred Qualifications:

• Experience working with natural language processing (NLP), semantic search, or large language models (LLMs)
• Hands-on experience with cloud-based services (AWS, Google Cloud, etc.), containers, and CI/CD pipelines
• Experience in high-frequency data environments or systematic trading

Pre-Application :

• Please do not apply if you're looking for a contract or remote work.
• You must be eligible to live and work in the US, without requiring sponsorship.
• Please ensure you meet the required experience section prior to applying.
• Allow 1-5 working days for a response to any job enquiry.
• Your application is subject to our privacy policy, found here:

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