Applied Machine Learning Scientist (Early Career)

OpenTable; Toronto; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

OpenTable is seeking an early-career Applied Machine Learning Scientist to join our team in Toronto. You will research and deploy machine learning models while working closely with a tight-knit group of experts. This position offers mentorship and the opportunity for personal growth in a dynamic environment focused on innovation and experimentation.

Benefits

Generous paid vacation

Mental health benefits

Paid parental leave

Employee Resource Groups

Private health and dental insurance

Life and Disability insurance

Qualifications

• Education including BSc, MSc, or PhD in relevant fields.
• Hands-on experience with ML models, training, and debugging.
• Strong programming skills in Python, familiarity with ML frameworks.

Responsibilities

• Research and deploy ML models for search and recommendations.
• Build data pipelines and ensure data quality.
• Design A/B tests and analyze results to inform product decisions.

Skills

Python proficiency

Machine Learning

Deep Learning

Communication

Collaboration

Education

BSc, MSc, or PhD in Computer Science, Statistics, or Mathematics

Tools

PyTorch

TensorFlow

JAX

NumPy

Pandas

scikit-learn

Job description

Applied Machine Learning Scientist (Early Career)

Hybrid - Toronto

This will be a remote role to start, with plans to transition to hybrid in-office 2x/week located in downtown Toronto.

**Please note: We are unable to provide visa sponsorship at this time.

Why this role at OpenTable?

OpenTable seats 25million diners each month across 60,000+ restaurants and taps into more than 20years of booking data—an ideal launchpad for an early‑career ML scientist. In our tight‑knit team, every experiment you run and every model you ship goes live quickly and at scale. You’ll start with well‑scoped projects and close mentorship, then rapidly earn the freedom to pitch and implement research ideas that deliver measurable value for diners, restaurants, and the business. We celebrate agency, speed, and relentless experimentation, balanced by disciplined prioritization rooted in ML expertise and real‑world production and business constraints.

Responsibilities:

• Research & Productionise Prototype, validate, and deploy ML models that power search, ranking, recommendations, pricing, and conversational recommendation systems.
• Data Pipelines Build reliable pipelines in PySpark; ensure reproducibility, lineage, and monitoring.
• Experimentation Design online A/B tests, define success metrics, and analyse results to inform product decisions and areas of further experimentation.
• Tooling & Best Practices Contribute to internal ML libraries for training, evaluation, debugging, and interpretation; champion code quality and reproducibility.
• Research Awareness Stay current with ML/RL literature, and constantly evaluate new models

Must‑Have Qualifications:

• Education Recently completed BSc, MSc, or PhD in Computer Science, Statistics, Mathematics, or a closely related technical field.
• Technical Skills
  • Hands-on experience training, tuning, and debugging both classical models (e.g., GBDTs) and deep-learning models (primarily Transformers).
  • Python proficiency and fluency with the scientific/ML stack: one of PyTorch/TensorFlow/JAX, core libraries (NumPy, Pandas, scikit‑learn), and at least one gradient‑boosting toolkit (XGBoost, LightGBM, or CatBoost).
  • Strong command of algorithms, data structures, and object‑oriented design.
• Applied ML Expertise
  • Detecting & mitigating target leakage, train‑test temporal skew, data drift, and other common pitfalls in building production models.
  • Translate business objectives into quantifiable ML metrics (e.g., MRR, MAP, precision/recall, AUC, F1, NDCG) and choose appropriate loss functions (e.g., Plackett–Luce, cross‑entropy, focal loss) to optimise them.
• High Agency & Ownership Demonstrated ability to identify opportunities, form hypotheses, and drive projects that align with business objectives with minimal supervision.
• Communication & Collaboration Clear written/verbal communication and a collaborative mindset.
• Reinforcement Learning Hands‑on RL experience—especially fine‑tuning LLMs toward verifiable objectives or applying RL/bandits in recommendation and ranking—is a strong plus.
• Domain Expertise Background in learning‑to‑rank, recommender systems, conversational agents, or NLP.
• Portfolio:Open‑source contributions, Kaggle medals, blogs or peer‑reviewed publications that replicate and extend academic research.
• Production ML Ops Experience with Spark, Airflow, Docker/Kubernetes, feature stores, and model observability/monitoring.

OpenTable strives to provide a fair, collaborative, and balanced work environment.

Benefits and Perks:

• Generous paid vacation + time off for your birthday
• Work from (almost) anywhere for up to 20 days per year
• Focus on mental health and well-being:
  • Company-paid therapy sessions through SpringHealth
  • Company-paid subscription to HeadSpace
  • Company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
• Paid parental leave
• Focus on your career growth:
  • Development Dollars
  • Leadership development
  • Access to thousands of on-demand e-learnings
• Travel Discounts
• Employee Resource Groups
• Private health and dental insurance
• Life and Disability insurance

There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. The range for this Toronto, Canada based role is $120,000-$150,000 CAD.

We offer a competitive base salary and benefits including: health benefits; flexible spending account; retirement benefits; life insurance; paid time off (including PTO, paid sick leave, medical leave, bereavement leave, floating holidays and paid holidays); and parental leave benefits. This role is eligible to be considered for an annual bonus and equity grant.

Diversity, Equity, and Inclusion

At OpenTable, we aspire to be a workplace that fosters inclusion and reflects the diverse communities we serve. Hiring people with different backgrounds and perspectives is critical to innovation and to how we deliver great experiences for our users, partners, and teams. We strive to be an open and welcoming environment so that no matter who you are, you can be yourself.

We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job responsibilities, and to receive other benefits and privileges of employment. Please contact us to request accommodation(s).

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