Staff Data Scientist – Remote-First ML & AI in Production

Remote; San Francisco (CA); Remote; USD 170,000 - 210,000; Full time

Benefits offered by this job

Health insurance

Profit sharing

Home office allowance

Employee assistance program

Extended parental leave

Job summary

Grupo QuintoAndar’s Data Science team seeks a skilled ML Engineer to architect, develop, and deploy ML systems for production. You’ll design experiments, analyze diverse data, and build LLM-powered features such as chatbots and search enhancements.

You will collaborate with product squads, share knowledge, and contribute to the Data Science chapter. Strong English communication and deep learning experience are essential.

Qualifications

• Proven knowledge of ML concepts: regression, classification, clustering, eval techniques.
• Strong Python proficiency for data science workflows and deployment.
• Experience with Deep Learning and ML model explainability.
• Familiarity with generative AI, LLMs, prompts, and evaluation.
• Excellent written and verbal technical communication skills.

Responsibilities

• Architect, develop and deploy ML systems to production focusing on chatbots and search.
• Design and run experiments to validate hypotheses and improve models.
• Analyze diverse data to improve existing models or create new ones.
• Apply scientific methods to develop LLM-powered applications, prompts, and guardrails.
• Contribute to Data Science chapter discussions, reviews, and demos.

Skills

Python

Machine Learning

Deep Learning

LLM / Generative AI

English communication

Education

MSc in ML / Data Science / NLP or related field

Job description

Grupo QuintoAndar’s Data Science team seeks a skilled ML Engineer to architect, develop, and deploy ML systems for production. You’ll design experiments, analyze diverse data, and build LLM-powered features such as chatbots and search enhancements.

You will collaborate with product squads, share knowledge, and contribute to the Data Science chapter. Strong English communication and deep learning experience are essential.