Applied AI ML, Associate
Salary not listed • New York, NY, United States • Full-time
Posted 1d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
Our goal is to build the next generation of AI: autonomous agents that can reason, plan, act, and learn to solve critical problems for an industry-leading financial institution. You will join a team transforming operations by leveraging advancements in agent-based AI and modern generative AI techniques. As an Applied Artificial Intelligence and Machine Learning Associate, you will contribute to building autonomous agent systems that solve high-impact business problems. You will help translate business needs into measurable outcomes by supporting applied research, model development, and enterprise-ready delivery. You will work in a collaborative environment that values ownership, learning, and responsible adoption of modern AI.
Responsibilities
- Build and enhance generative AI and agent-based solutions for workflow automation.
- Translate business problems into technical approaches, success metrics, and experiment plans.
- Develop and test agent workflows for planning, tool-use, and orchestration.
- Implement reusable components to accelerate applied AI delivery.
- Execute rigorous evaluation practices, including offline/online testing and error analysis.
- Partner with stakeholders to gather requirements, communicate tradeoffs, and support production readiness.
- Contribute to responsible scaling by considering reliability, security, and operational constraints.
Requirements
- Formal training or certification in applied AI/ML with 2+ years of applied experience.
- Bachelor's degree in Computer Science, Engineering, Statistics, or a related quantitative field (or equivalent practical experience).
- Hands-on experience building production-grade software in Python, including testing, refactoring, and version control.
- Experience applying ML methods to real-world problems and evaluating results with reproducible metrics.
- Experience deploying or supporting services in a cloud environment with attention to reliability, observability, and latency.
- Strong fundamentals in software engineering (data structures, algorithms, object-oriented design) and problem-solving.
- Strong communication and collaboration skills with technical and non-technical partners.