TL;DR

Staff Data Scientist (AI): Leading the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization with an accent on owning the full machine learning lifecycle from problem framing to deployment and monitoring. Focus on designing and implementing advanced ML/statistical models that improve product performance and driving business value through data science initiatives.

Location: Remote, United States

Salary: $143,000–$229,000 USD

Company

%hirify_global% creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

What you will do

Lead the design and development of scalable ML systems for various use cases.
Own the full machine learning lifecycle from problem framing to deployment and monitoring for mission-critical initiatives.
Design and implement advanced ML and statistical models to improve product performance and customer insights.
Collaborate with engineers, product managers, and business stakeholders to define project scope and integration strategy.
Guide architectural decisions, set modeling standards, and champion best practices for ML productionization.
Proactively identify areas where data science can create business value and lead cross-functional efforts.

Requirements

10+ years of experience in data science with a proven track record of delivering production ML systems.
Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.
Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.
Experience with distributed data processing and training, real-time inference, and MLOps frameworks.
Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).
Hands-on experience with AWS cloud platforms (including SageMaker, Athena, Glue, DynamoDB, and Bedrock).

Nice to have

An advanced degree in Computer Science, Statistics, or a related STEM field.
Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.
Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF).

Culture & Benefits

Competitive compensation and benefits programs, including cash compensation, benefits, and equity.
Opportunity to learn new AI tools to build faster, more independently, and with higher quality.
We strive to provide means to a healthy lifestyle with flexibility.
Commitment to Diversity, Equity, and Inclusion.
Embrace a hybrid work model for in-person collaboration while valuing individual needs (company-wide).