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Applied Machine Learning Scientist II

Toronto, Canada

Pay
CAD 170,000–190,000/yearAnnual period assumed · Location-specific pay · Includes commission — pay source
The best connections happen face-to-face, whether you’re sitting down to dinner or having coffee with a coworker. That’s why OpenTable has adopted a hybrid workplace model. This role aligns with that approach, with an expectation of coming into the office two days a week—giving employees the best of both worlds: in-person collaboration and flexibility. The expected range of compensation for this position based in Toronto, Canada, including commission and/or bonuses is $170,000 - $190,000 CAD. There are a variety of factors that go into determining a compensation range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. 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.
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Work setup
Unconfirmed
Employment
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What you’ll work on

Full posting
  • Build and monitor scalable data and machine learning pipelines, ensuring strong data quality and reproducibility.

  • Design evaluation frameworks and experiments to define success metrics and continuously improve model quality, relevance, and product impact.

  • Develop reusable machine learning tooling and maintain rigorous standards for code quality, deployment, and documentation.

From the employer’s posting
Prototype, evaluate, and productionize machine learning systems to enhance restaurant content understanding, retrieval, matching, ranking, and recommendation. Build and monitor scalable data and machine learning pipelines, ensuring strong data quality and reproducibility. Design evaluation frameworks and experiments to define success metrics and continuously improve model quality, relevance, and product impact.
Build and monitor scalable data and machine learning pipelines, ensuring strong data quality and reproducibility. Design evaluation frameworks and experiments to define success metrics and continuously improve model quality, relevance, and product impact. Apply large language models (LLMs) and multimodal approaches to content tasks like extraction and classification while optimizing for performance, latency, and cost.
Apply large language models (LLMs) and multimodal approaches to content tasks like extraction and classification while optimizing for performance, latency, and cost. Develop reusable machine learning tooling and maintain rigorous standards for code quality, deployment, and documentation. Collaborate cross-functionally with engineering, product, and content teams to translate ambiguous business needs into practical, scalable machine learning solutions.

What you’ll bring

All qualifications

Core experience

  • Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field, with 0-3 years of relevant academic or professional experience.
  • Proficiency in Python and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost).
  • Hands-on experience training, tuning, evaluating, and debugging classical machine learning and deep learning models, including Transformers.
  • Demonstrated ability to translate business goals into machine learning metrics and address common production issues like data drift and overfitting.

Preferred experience

  • Experience applying machine learning to text, image, or multimodal content for retrieval, matching, ranking, or recommendation.
  • Familiarity with large language model (LLM) workflows for text and image processing tasks.
  • Experience with human-in-the-loop machine learning systems supporting operational or editorial workflows.
Qualification wording
Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field, with 0-3 years of relevant academic or professional experience.
Proficiency in Python and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost).
Hands-on experience training, tuning, evaluating, and debugging classical machine learning and deep learning models, including Transformers.
Demonstrated ability to translate business goals into machine learning metrics and address common production issues like data drift and overfitting.
Experience applying machine learning to text, image, or multimodal content for retrieval, matching, ranking, or recommendation.
Familiarity with large language model (LLM) workflows for text and image processing tasks.
Experience with human-in-the-loop machine learning systems supporting operational or editorial workflows.
Education & alternatives
Minimum Qualifications - Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field, with 0-3 years of relevant academic or professional experience. - Proficiency in Python and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost).

Tools in this posting

  • Python
  • PyTorch
  • TensorFlow
  • scikit-learn
  • Xgboost
Source — Tool mentions in context
- Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field, with 0-3 years of relevant academic or professional experience. - Proficiency in Python and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost). - Hands-on experience training, tuning, evaluating, and debugging classical machine learning and deep learning models, including Transformers.

Benefits in the posting

Full benefits wording
  • Generous paid vacation + time off for your birthday
  • Focus on mental health and well-being:
  • Company-paid therapy sessions through SpringHealth
  • Company-paid subscription to Headspace
  • Paid parental leave
  • Paid volunteer time
  • Focus on your career growth:
  • Development Dollars
  • Leadership development
  • Access to thousands of on-demand e-learnings
  • Travel Discounts
  • Employee Resource Groups
  • 20 days of paid time off
  • Private health and dental insurance
  • Life and Disability insurance
  • 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.
  • Inclusion

From the employer’s posting.

Job description

View original posting ↗

This hybrid role requires working in the office two days per week.

With millions of diners, 70,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most – their team, their guests, and their bottom line – while enabling diners to discover and book the perfect restaurant for every occasion. 

Every employee at OpenTable has a tangible impact on what we do and how we do it. You’ll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.

Why this role at OpenTable?

OpenTable seats 25 million diners each month across 70 000+ restaurants and taps into more than 20 years 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. This posting is for an existing vacancy.

Responsibilities

  • Prototype, evaluate, and productionize machine learning systems to enhance restaurant content understanding, retrieval, matching, ranking, and recommendation.
  • Build and monitor scalable data and machine learning pipelines, ensuring strong data quality and reproducibility.
  • Design evaluation frameworks and experiments to define success metrics and continuously improve model quality, relevance, and product impact.
  • Apply large language models (LLMs) and multimodal approaches to content tasks like extraction and classification while optimizing for performance, latency, and cost.
  • Develop reusable machine learning tooling and maintain rigorous standards for code quality, deployment, and documentation.
  • Collaborate cross-functionally with engineering, product, and content teams to translate ambiguous business needs into practical, scalable machine learning solutions.

Minimum Qualifications

  • Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field, with 0-3 years of relevant academic or professional experience.
  • Proficiency in Python and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost).
  • Hands-on experience training, tuning, evaluating, and debugging classical machine learning and deep learning models, including Transformers.
  • Strong foundation in software engineering principles, algorithms, and data structures, with familiarity in large-scale data systems.
  • Demonstrated ability to translate business goals into machine learning metrics and address common production issues like data drift and overfitting.

Preferred Qualifications

  • Experience applying machine learning to text, image, or multimodal content for retrieval, matching, ranking, or recommendation.
  • Familiarity with large language model (LLM) workflows for text and image processing tasks.
  • Exposure to search systems, information retrieval, embeddings, or learning-to-rank methodologies.
  • Experience with human-in-the-loop machine learning systems supporting operational or editorial workflows.
  • Demonstrated applied curiosity through substantial technical projects, research, open-source contributions, or internships.

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
    • Annual company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
  • Paid parental leave
  • Paid volunteer time
  • Focus on your career growth:
    • Development Dollars
    • Leadership development
    • Access to thousands of on-demand e-learnings
  • Travel Discounts
  • Employee Resource Groups
  • 20 days of paid time off
  • Private health and dental insurance
  • Life and Disability insurance

The best connections happen face-to-face, whether you’re sitting down to dinner or having coffee with a coworker. That’s why OpenTable has adopted a hybrid workplace model. This role aligns with that approach, with an expectation of coming into the office two days a week—giving employees the best of both worlds: in-person collaboration and flexibility.

The expected range of compensation for this position based in Toronto, Canada, including commission and/or bonuses is $170,000 - $190,000 CAD. There are a variety of factors that go into determining a compensation range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required.

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.

Work Environment & Flexibility

At OpenTable, we pride ourselves on fostering a global and dynamic work environment. As a team member with us, you will benefit from a schedule tailored to accommodate a global workforce operating across multiple time zones. While the majority of your responsibilities may align with conventional business hours, there will be instances where you are expected to manage communications - via calls, Slack messages, or emails - outside of regular working hours to effectively collaborate with international colleagues, respond to restaurant partners, and/or address urgent matters. OpenTable will always abide by and consider local laws and regulations.

Inclusion

We’re committed to creating a workplace where everyone feels they belong and can thrive. We know the best ideas come when we bring different voices to the table, so we're building a team as dynamic as the diners and restaurants we serve—and fostering a culture where everyone feels welcome to be themselves.

If you need accommodations during the application or interview process, or on the job, we’re here to support you. Please reach out to your recruiter to request any accommodations.

#LI-LR1

#LI-Hybrid

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Source & posting history

View original posting ↗

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Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
The best connections happen face-to-face, whether you’re sitting down to dinner or having coffee with a coworker. That’s why OpenTable has adopted a hybrid workplace model. This role aligns with that approach, with an expectation of coming into the office two days a week—giving employees the best of both worlds: in-person collaboration and flexibility. The expected range of compensation for this position based in Toronto, Canada, including commission and/or bonuses is $170,000 - $190,000 CAD. There are a variety of factors that go into determining a compensation range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. 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.
Location & working pattern

Toronto, Canada

This hybrid role requires working in the office two days per week. With millions of diners, 70,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most – their team, their guests, and their bottom line – while enabling diners to discover and book the perfect restaurant for every occasion.
More source context
- Life and Disability insurance The best connections happen face-to-face, whether you’re sitting down to dinner or having coffee with a coworker. That’s why OpenTable has adopted a hybrid workplace model. This role aligns with that approach, with an expectation of coming into the office two days a week—giving employees the best of both worlds: in-person collaboration and flexibility. The expected range of compensation for this position based in Toronto, Canada, including commission and/or bonuses is $170,000 - $190,000 CAD. There are a variety of factors that go into determining a compensation range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required.

More relevant text appears in the full description.

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Status in our records
Active
First seen by us
Sep 4, 2026
Recorded sightings
24
Last seen by us
Oct 8, 2026

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