Senior Applied Scientist, Agentic AI

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of complex applied-science challenges from start to finish, including opportunity identification, hypothesis formulation, data analysis, modeling, experimentation, and production refinement.

• Develop and assess machine learning and LLM-based strategies to enhance customer experiences.

• Set meaningful baselines, leverage pertinent research, and introduce complexity when supported by data.

• Create dependable datasets and conduct offline evaluations.

• Design online experiments that link model quality to significant customer and business outcomes.

• Collaborate with engineering, product, design, and science teams to convert methods into dependable production capabilities.

• Ensure a balance between quality, safety, latency, and cost.

• Write maintainable code in Python and SQL.

• Contribute scientific components that are ready for production.

• Communicate methods, insights, and technical decisions with scientists and engineers.

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Statistics, Mathematics, Electrical Engineering, or a related quantitative field, along with 8+ years of experience applying machine learning or advanced statistical modeling in an industry setting, including production delivery; or an equivalent combination of education and experience.

• Strong foundation in applied machine learning and statistics.

• Expertise in recommendations, ranking, search, personalization, or conversational AI.

• Experience working with large-scale datasets, conducting experiments or A/B testing, and measuring model performance.

• Understanding of data quality, bias, uncertainty, and causal impact.

• Practical knowledge of LLM-based systems, including context, generation, evaluation, and limitations.

• Proficient in Python and SQL.

• Ability to develop tested, reusable code that is integrated for production use.

• Strong technical communication skills and a proven record of collaboration with engineering, product, and science partners.

• Experience with recommendation, ranking, or personalization systems is a plus.

• Extensive hands-on experience in building and evaluating LLM-based or agentic systems in production is a plus.

• Experience with model distillation, supervised fine-tuning, preference optimization, or small-model deployment is a plus.

• Familiarity with evaluating multi-turn conversations, recommendation sets, session quality, or long-term customer outcomes is a plus.

• Knowledge of large consumer marketplaces, sparse and delayed outcomes, cold-start scenarios, or real estate is a plus.

• Contributions to research that adapt new methods to real-world challenges are a plus.

🏝️ Benefits

• Equity awards based on factors such as experience, performance, and location.

• Option to work remotely from a location of your choice.

• Flexible distributed work opportunities through Cloud HQ.

• Commitment to equal employment opportunity and an inclusive work environment.