Software AI Engineer
About the Firm
We are a world-class investment management firm headquartered in Boston, known for applying advanced technology and data-driven approaches to generate superior returns across global markets. Our culture emphasizes intellectual rigor, innovation, and collaboration. We are building next-generation systems that leverage artificial intelligence to inform investment decisions, streamline operations, and unlock new research capabilities.
The Opportunity
We're seeking a highly skilled Software AI Engineer to join our growing AI & Investment Technology team. You'll be responsible for building production-grade AI systems that are deeply integrated with our investment and research platforms. This is a high-impact, hands-on engineering role with exposure to cutting-edge models, rich datasets, and real-world financial challenges.
Key Responsibilities
Develop and deploy scalable AI solutions for research, portfolio management, and operational efficiency.
Work closely with data scientists, quants, and investment professionals to translate research models into robust production systems.
Design and maintain high-performance pipelines for data processing, model training, and real-time inference.
Contribute to the design of internal AI platforms and tools that support experimentation and deployment at scale.
Stay current on the latest AI and software engineering developments and assess their potential for adoption.
Ensure the reliability, security, and observability of AI-driven services running in production environments.
Ideal Qualifications
4+ years of experience as a software engineer, with a strong focus on AI/ML systems in production.
Deep proficiency in Python, with experience in frameworks such as PyTorch, TensorFlow, or JAX.
Strong software engineering fundamentals (data structures, distributed systems, cloud-native architectures).
Experience deploying and maintaining ML/AI models in real-world settings (batch and real-time inference).
Familiarity with MLOps practices and tools (Docker, Kubernetes, MLflow, etc.)
Passion for clean, testable, and maintainable code.
Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
Exposure to financial markets, trading systems, or quantitative research is a plus-but not required.
FAQs
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