Senior Associate-Applied Artificial Intelligence / Machine Learning
Salary not listed • Palo Alto, CA, United States • Full-time
Posted 18h ago
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Job Location
Palo Alto, CA, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
Join an Applied Artificial Intelligence and Machine Learning team that takes Generative AI and Machine Learning applications from prototype to production for a Global Banking business. You will work in a collaborative, inclusive environment with opportunities to build technical depth. As a Senior Associate–Applied Artificial Intelligence / Machine Learning, you will help solve exciting business challenges for a Global Banking business within a leading global financial institution. You will work with product, business, and engineering partners to turn business problems into AI/ML solutions, balancing accuracy, latency, cost, and risk, and deliver them reliably in a regulated environment. You will apply sound technical judgment to balance business needs with technical constraints, contribute to experimentation and validation, and help productionize scalable and trustworthy solutions. You will also engage in knowledge sharing through enterprise machine learning communities.
Responsibilities
- Collaborate with an AI/ML team to contribute to projects within a global organization and support an inclusive culture.
- Assist in setting the technical vision and executing strategic roadmaps to drive AI innovation.
- Design, build, and iterate on generative AI and machine learning applications.
- Evaluate LLM-powered applications using curated test sets, metrics, automated and LLM-based scoring, human review, and regression testing, and use the results to drive improvements.
- Partner with engineering teams to productionize solutions, and monitor quality, latency, and cost once deployed.
- Work with product and business partners to translate requirements into AI/ML specifications, define milestones, and deliver using Agile methodology.
- Apply responsible AI practices, including explainability, and meet model risk and governance requirements in a regulated environment.
Requirements
- Three years of experience developing AI/ML applications, with an advanced degree in Computer Science, Data Science, Statistics, or an equivalent field, or equivalent practical experience.
- Hands-on experience building applications with LLMs, including prompt engineering, context management, and output parsing.
- Experience evaluating AI/ML systems, including designing metrics, test sets, and experiments for non-deterministic outputs.
- Knowledge of data structures, algorithms, machine learning, data mining, and information retrieval.
- Hands-on experience applying classical machine learning (e.g., linear models, tree-based ensembles, clustering) and deep learning (e.g., neural networks, transformers), including feature engineering, model training, and validation.
- Proficiency in Python with hands-on experience in machine learning and deep learning frameworks (PyTorch, scikit-learn) and generative AI ecosystems (Hugging Face, LLM APIs, LangChain/Google ADK).
- Experience using version control, code review, and testing practices.
- Collaboration skills and the ability to communicate effectively with both technical and non-technical audiences.