Senior Applied ML Scientist (Recommendation And Ranking)
OpenTable
- Vancouver, BC
- $147,000-200,000 per year
- Permanent
- Full-time
- As the premier online restaurant reservation provider, OpenTable facilitates over 25 million diner reservations monthly across roughly 60,000 restaurants worldwide, backed by an extensive database of diner and restaurant information spanning over two decades.
- Despite OpenTable's extensive reach, our team remains agile, with just over 1,000 employees globally, including a compact ML team of nine members, eager to expand.
- Researching and developing ML models, as well as collaborating with engineers to productionize them
- Engineering new features and implementing data pipelines that enhance ML models.
- Designing and analyzing the outcomes of online experiments.
- Contributing to the internal ML libraries and assisting in the development of tools for training, evaluation, debugging, and interpretation of models.
- Keeping abreast of ML research to apply its advancements effectively and communicate these to your colleagues.
- Have a profound understanding of and experience in Machine Learning, including:
- Algorithms (e.g., Deep Learning, NLP, GBDT)
- Evaluation Metrics (e.g., precision, recall, AUC) and the design of effective metrics evaluations
- Loss Functions (e.g., Categorical Cross-Entropy, Hinge, Focal, etc.)
- Standard Practices (e.g., preventing data leakage, avoiding overfitting, encoding categorical features for Deep Learning or GBDT models)
- Possess knowledge of data structures, algorithms, and object-oriented design
- Have a strong proficiency in Python and practical experience with ML/scientific computing libraries (NumPy, SciPy, Pandas, XGBoost, TensorFlow/PyTorch)
- Are committed to continuous learning and self-improvement
- Exhibit excellent communication skills and the ability to collaborate effectively within a team environment
- Experience in one or more of the following areas: learning to rank, recommendations, NLP/LLM, computer vision
- Participation in a Machine Learning project or contribution to an open-source ML library demonstrating your research, implementation, and evaluation capabilities based on academic papers, or relevant publications
- A track record in Machine Learning projects or Kaggle competitions showing your ability to analyze data, innovate features, and enhance ML model performance significantly beyond basic benchmarks
- Familiarity with reinforcement learning, multi-armed bandit algoritms
- Experience with Spark, SQL, and Airflow
- A graduate degree in ML, Mathematics, Statistics, Physics, Economics, or a related technical field
- Some Java experience
- Paid Time Off - 20 days a year
- Birthday/celebration PTO - 1 day
- Flexible sick time off
- Paid volunteer time
- Annual company week off
- Parental Leave Benefits
- Dental & Vision Insurance
- Life & Disability Insurance
- Group RRSP and DPSP
- Major Medical Insurance (dependent care options)