Overview Join Millennium's Data Science team to build and deploy production-grade AI and ML solutions that power multi-manager analytics and trading capabilities. You will translate research into scalable, real-time and batch data workflows, collaborating with product managers, data engineers, and business stakeholders. You'll evaluate new techniques, design robust evaluation frameworks, and maintain high-quality code and documentation. This role offers the chance to drive impact through cutting-edge AI within a global investment environment that values learning and collaboration.
Compensation / Benefits- base salary
- discretionary performance bonus
- comprehensive benefits
Responsibilities- Build, test, and deploy production-grade AI and ML solutions using classical methods and generative approaches, including LLMs and agentic workflows.
- Conduct applied research to identify practical AI/ML opportunities for business problems.
- Design evaluation frameworks to measure model quality, robustness, and business impact.
- Collaborate with product managers, data engineers, and stakeholders to translate research into scalable solutions.
- Contribute to data pipeline workflows and support monitoring, guardrails, and human-in-the-loop processes.
- Communicate technical concepts and findings to diverse audiences.
- Stay current with AI/ML developments and apply relevant advances thoughtfully.
- Maintain high standards for code quality, documentation, and review practices.
Key requirements- 3+ years of industry or applied research experience with an MS or PhD in a related STEM field.
- Strong foundation in ML, DL, NLP, statistics, algorithms, and data structures.
- Hands-on experience building/deploying AI/ML solutions, incl. LLMs, generative AI, prompt engineering, RAG, fine-tuning, and agentic systems.
- Strong Python skills with PyTorch, TensorFlow, JAX, or scikit-learn.
- Familiarity with LLM/AI frameworks like Hugging Face, LangChain, and LlamaIndex.
- Experience with at least one cloud platform, vector databases, big data ecosystems, and MLOps/LLMOps tooling.
- Exposure to AI-assisted coding tools such as Claude, Codex, GitHub Copilot, or Cursor.
- Strong communication, sound judgment, independence, and ability to learn quickly in a fast-moving environment.
- strong communication
- sound judgment
- independence
- machine learning
- deep learning
- natural language processing
