Senior Machine Learning Engineer - Applied Modeling (TakeUp)

About Us

TakeUp, LLC is revolutionizing revenue optimization for hospitality with a daring approach to pricing. Using AI and machine learning, TakeUp empowers independent operators to unlock maximum revenue potential through pricing courageously—day in, day out. Seamlessly integrated with top Property Management Systems, our platform replaces traditional rate-setting constraints with data-driven confidence, delivering an impressive 10-15x ROI.

The Opportunity

We are hiring a Senior Machine Learning Engineer to focus on applied modeling for our rate optimization engine. This role is hands-on: designing, training, and deploying models that turn hotel data into reliable production outcomes. You will collaborate closely with the ML Engineering Manager, the CTO, and product partners to design modeling approaches, build pipelines, and support experiments that drive measurable revenue impact.

What You’ll Do

Modeling

• Design, train, and deploy production ML models, with emphasis on tree-based methods (XGBoost, LightGBM, CatBoost).
• Contribute to feature engineering and model evaluation approaches that balance accuracy, interpretability, and speed.
• Translate customer needs and product requirements into practical modeling tasks (classification, regression, ranking, uplift).
• Develop custom performance metrics to evaluate models’ ability to generate reasonable counterfactual demand estimates while accounting for varying customer product expectations.
• Support explainability efforts to justify rate decisions with clear artifacts and documentation.

Pipelines & Deployment

• Build and maintain training and evaluation pipelines, ensuring offline metrics align with online business outcomes.
• Partner with engineering to integrate models into production services and batch jobs with defined SLAs.
• Contribute production ready Python and SQL code with strong testing and review practices.
• Support data quality, observability, and reproducibility across the ML lifecycle.

Experimentation

• Collaborate on experiment design, including A/B testing and staged rollouts.
• Implement policy guardrails to ensure automated rate changes are safe and controlled.
• Analyze experimental results, communicate lift and trade-offs, and document findings.

Collaboration

• Work closely with product, engineering, and leadership to scope problems and propose modeling approaches.
• Participate in code reviews, model reviews, and planning sessions.
• Share learnings and contribute to improving team practices around modeling, metrics, and documentation.

Who You Are

• 4+ years of experience building and deploying ML models to production.
• Proficiency in Python (scikit-learn, XGBoost/LightGBM/CatBoost).
• Strong SQL skills and comfort with large, imperfect, real-world datasets.
• Experience across the full model lifecycle: data preparation, feature engineering, training, evaluation, deployment, and monitoring.
• Familiarity with experimentation design and metrics; able to reason about trade-offs and safeguards.
• Clear communicator, comfortable working in a collaborative, fast-paced environment.

Nice to Have

• Experience with causal inference (uplift modeling, causal forests, DML) or time-series modeling.
• Exposure to reinforcement learning concepts (multi-armed bandits, dynamic programming, temporal-difference learning).
• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and dbt.
• Familiarity with orchestration frameworks (Prefect, Airflow).
• Familiarity with MLOps frameworks (Sagemaker, Vertex AI)
• Domain knowledge in pricing, demand modeling, or hospitality.
• Former start-up experience.

Why TakeUp?

At TakeUp, we empower our team to innovate, grow, and succeed. You’ll join a passionate group of professionals who are committed to changing the way businesses run. This is mission-driven work: we’re empowering independent inns and small hotels, businesses often underserved and outgunned by enterprise competitors, with technology that levels the playing field.

Ready to take your career to the next level with a fast-growing SaaS company? Apply now and let's make an impact together!

Travel

This role is remote. While flexibility is key, we also value in-person connections. Travel may be needed for customer discovery, team building, and/or networking.