About Medusa
Medusa is a boutique AI consultancy helping hedge funds, asset managers, and family offices deploy production-grade AI systems in investment, risk, and reporting workflows. We specialize in agentic AI solutions operating in complex, data-intensive, and decision-critical environments.
Role
We are looking for an experienced AI Engineer to design and implement applied AI systems for investment and risk-management use cases.
The role is hands‑on and spans AI engineering, financial data systems, and production delivery, rather than pure academic research. The position requires the ability to operate in low signal‑to‑noise environments, where correctness, explainability, and robustness are critical.
This is an individual‑contributor role in a small, highly technical team.
The role may initially start on a project or probationary basis, depending on candidate profile and project pipeline.
Key Responsibilities
* Build agentic AI applications combining LLMs, structured financial data, and internal investment tools
* Design and implement end‑to‑end AI workflows (data ingestion, orchestration, inference, monitoring)
* Develop production‑ready prototypes and MVPs for professional investment teams
* Integrate AI systems with existing portfolio, risk, and reporting platforms
* Translate complex investment and risk workflows into robust AI systems
* Collaborate directly with the Founder on solution architecture and client delivery
Required Qualifications
* MSc or PhD in Computer Science, Data Science, Applied Mathematics, or a closely related field
* Strong hands‑on experience in applied machine learning and AI engineering
* Excellent Python skills; experience with modern ML frameworks (e.g. PyTorch)
* Proven experience building scalable data and ML pipelines (cloud, containers, orchestration)
* Experience deploying AI systems into production or mission‑critical environments
* Ability to independently design systems across research, engineering, and deployment
Strongly Preferred
* Prior exposure to financial markets, risk management, or investment workflows
* Background in production ML or large‑scale data platforms
* Experience working at the intersection of advanced ML research and real‑world deployment
What We Offer
* Work on real‑world AI systems used by professional investment teams
* High technical autonomy and end‑to‑end ownership
* Close collaboration with a founder with deep finance and technology background
* Competitive compensation with performance‑based components
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