- Company Name
- Cerberus Capital Management
- Job Title
- AI Engineer
- Job Description
-
**Job title:** AI Engineer
**Role Summary**
Design, develop, and deploy production‑grade machine learning solutions that directly influence investment decisions and portfolio performance. Work in an agile, cross‑functional environment, rapidly iterating from prototype to fully integrated AI products.
**Expectations**
- Deliver models that are not only trained but actively deployed, monitored, and adopted by business users.
- Measure and report tangible business impact (e.g., acceleration of due diligence, improved deal sourcing).
- Collaborate closely with investment desks, portfolio teams, and engineering counterparts to embed AI tools into existing workflows.
- Maintain high standards of code quality, documentation, and operational reliability.
**Key Responsibilities**
- Architect AI pipelines for NLP, forecasting, computer vision, or optimization as required by investment scenarios.
- Build, test, and deploy ML models using APIs or microservices; manage model lifecycle (versioning, monitoring, rollback).
- Prototype and roll out Generative‑AI solutions for due diligence and automated deal‑sourcing workflows.
- Integrate third‑party APIs, clean and transform data, and convert insights into structured, actionable outputs.
- Conduct proof‑of‑value pilots, analyze results, and iterate to refine model performance and user adoption.
- Communicate technical findings to both technical and non‑technical stakeholders via concise reports and dashboards.
**Required Skills**
- **Programming:** Python (type hints, production coding), NumPy, pandas/polars, scikit‑learn, XGBoost, LightGBM, PyTorch, JAX.
- **Data & SQL:** Proficient SQL; design efficient queries and data pipelines.
- **MLOps & Deployment:** Experience with MLflow, Weights & Biases, model versioning, experiment tracking, API/web‑service development (FastAPI, Flask).
- **Infrastructure:** Cloud platforms (Azure preferred; AWS or GCP), Docker, Kubernetes, Terraform.
- **Software Engineering:** CI/CD pipelines, automated testing, code review, Git, Azure DevOps.
- **LLM & AI Agents:** Working knowledge of LLM APIs (OpenAI, etc.) and lightweight AI agent construction; familiarity with orchestration tools (e.g., Temporal) is a bonus.
- **Soft Skills:** Strong problem‑solving, intellectual curiosity, pragmatic mindset, excellent written and verbal communication, ability to thrive in a fast‑moving environment.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in a STEM field (Computer Science, Engineering, Statistics, Math, or equivalent professional experience).
- No mandatory certifications required, but knowledge of relevant ML‑ops tools and cloud services is essential.
New york city, United states
On site
28-01-2026