- Company Name
- Millennium
- Job Title
- AI Engineer Lead
- Job Description
-
**Job Title:** AI Engineer Lead
**Role Summary**
Lead the design, development, and production of advanced AI/ML systems—including LLMs, deep learning, and reinforcement learning—within a financial services context. Drive technical strategy, mentor a multidisciplinary team, and deliver scalable, high‑performance models and infrastructure that enable portfolio managers, researchers, and risk teams to derive actionable insights.
**Expectations**
- Set and communicate a clear AI/ML vision aligned with business goals;
- Manage end‑to‑end model lifecycle: experimentation, training, deployment, monitoring, and re‑training;
- Build and maintain robust AI infrastructure (feature stores, deployment pipelines, MLOps);
- Mentor and grow engineering talent;
- Deliver projects on schedule while maintaining high quality and best‑practice standards;
- Stay current with AI/ML research and translate it into practical solutions.
**Key Responsibilities**
- Lead, mentor, and grow a team of AI/ML engineers;
- Define technical vision & roadmap for AI initiatives;
- Partner with portfolio managers, quants, and business units to identify high‑impact projects;
- Architect scalable AI/ML solutions from prototype to production;
- Design AI/ML infrastructure (data pipelines, feature store, deployment frameworks, monitoring systems);
- Establish best practices for model development, validation, deployment, and evaluation;
- Conduct research on emerging AI/ML techniques (LLMs, prompt engineering, PEFT, RAG, RL, etc.) and apply them to business challenges;
- Drive hiring, onboarding, performance reviews, and professional development;
- Communicate progress and insights to technical and non‑technical stakeholders.
**Required Skills**
- Deep expertise in LLMs, NLP (prompt engineering, fine‑tuning, PEFT, RAG) and reinforcement learning;
- Strong background in deep learning, computer vision, and algorithmic trading modeling;
- Proficient in Python and at least one other language (Java, C++, C#);
- Hands‑on experience with cloud platforms (AWS, Azure, or GCP) for ML workloads;
- Proven MLOps experience: model serving, CI/CD, monitoring, automatic re‑training pipelines;
- Leadership: ≥3 years leading AI/ML teams, mentoring engineers, and delivering complex projects;
- Excellent communication and stakeholder‑management skills.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, or related field.
- Preferred: Master’s or Ph.D. in Computer Science, AI, ML, or a quantitative discipline.
- Preferred certifications: AWS Certified Machine Learning – Specialty, Azure Machine Learning, or GCP Professional Machine Learning Engineer.