markham, on deep learning engineer Jobs – 61 Openings This Week

Data Science Manager, Rider Experience
Lyft —Toronto, ON
- $172,000–$215,000 a year
- Hybrid work
- Management
- Doctoral degree
- Computer Science
- Commuter benefits
- Dental care
Applied Scientist II
Coalition, Inc. —Toronto, ON
- $103,800–$129,690 a year
- Remote
- Doctoral degree
- Computer Science
- Master's degree
- Dental care
- Paid time off
Quick apply
Senior AI Engineer
ShyftLabs —Toronto, ON
- $120,000–$160,000 a year
- Full-time
- Hybrid work
- Computer Science
- Master's degree
- SQL
- Dental care
- Vision care
Quick apply
AI Development Engineer - Remote
NTT Ltd —Toronto, ON
- Full-time
- Hybrid work
- Azure
- Computer Science
- Engineering
Generative AI Software Engineer
Apertera —Toronto, ON
- Full-time
- Hybrid work
- Azure
- Computer Science
- DevOps
- Dental care
- Vision care
Quick apply
15h
Principal AI Engineer - AI Engineering & Enablement
Questrade Financial Group —Toronto, ON
- $115,000–$170,000 a year
- Full-time
- Hybrid work
- Computer Science
- Engineering
- Master's degree
Quick apply
Senior ML Engineer
Invoca —Toronto, ON
- $152,000–$228,000 a year
- Remote
- Computer Science
- Engineering
- Travel
- Dental care
- Paid time off
Quick apply
13d
Machine Learning Lead, Edge AI Inferencing
Blumind —Markham, ON
- Full-time
- Hybrid work
- Doctoral degree
- Computer Science
- Engineering
Quick apply
Data Scientist II
Scribd, Inc. —Toronto, ON
- $118,000–$123,000 a year
- Full-time
- Computer Science
- Master's degree
- SQL
- Disability insurance
- Dental care
Senior AI Engineer - AI Engineering & Enablement
Questrade Financial Group —Toronto, ON
- $120,000–$140,000 a year
- Full-time
- Hybrid work
- Computer Science
- Engineering
- Master's degree
Quick apply
Data Scientist, AI Deployment
Braze —Toronto, ON
- $112,000–$188,000 a year
- Hybrid work
- Doctoral degree
- Computer Science
- DevOps
- Dental care
- Paid time off
Quick apply
Staff AI Engineer
Acquia —Toronto, ON
- Remote
- Computer science
- Azure
- Computer Science
Quick apply
14d
AI Engineering Lead
Definity Financial Corporation —Toronto, ON
- $108,700–$158,700 a year
- Full-time
- Hybrid work
- Doctoral degree
- Computer Science
- Java
- Tuition reimbursement
- Paid time off
Senior AI Engineer
Robots and Pencils —Toronto, ON
- Remote
- Databases
- AWS
- APIs
Quick apply
Applied Scientist, Sales AI
Amazon Development Centre Canada ULC —Toronto, ON
- $149,300–$249,300 a year
- Full-time
- Doctoral degree
- Computer Science
- Java
- Profit sharing
- Dental care
Applied Scientist, Measurement, Ad Tech, and Data Science (MADS)
Amazon Development Centre Canada ULC —Toronto, ON
- $149,300–$249,300 a year
- Full-time
- Doctoral degree
- Computer Science
- Sales
- Profit sharing
- Dental care
Senior Applied Scientist, Measurement, Ad Tech, and Data Science (MADS)
Amazon Development Centre Canada ULC —Toronto, ON
- $195,900–$327,200 a year
- Full-time
- Doctoral degree
- Computer Science
- Sales
- Profit sharing
- Dental care

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Data Science Manager, Rider Experience

Lyft -
Toronto, ON

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Job details

$172,000–$215,000 a year

Qualifications

Statistics
Management
Doctoral degree
Computer Science
Master's degree
Analysis skills
Presentation skills
Machine learning
Communication skills

Full job description

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Data Science & Analytics is at the heart of Lyft's products and decision-making. The Rider Experience team sits at the center of how millions of riders discover, choose, and return to Lyft. We are hiring a Data Science Manager to lead our Toronto-based science & analytics team that turns rider behavior into product strategy. This role owns the analytical foundation behind our most consequential rider-facing decisions: how we measure experience quality, where friction costs us retention, and which bets move rider LTV. You will set the measurement and experimentation standards for rider product squads, and translate ambiguous business questions into rigorous, decision-ready analysis that shapes roadmap and investment.

You will also lead the team's transition to AI-native data science and analytics workflows, embedding AI tooling into how we explore data, make decisions, and ship products.

Responsibilities:

Lead and grow a high-performing team of data scientists and analysts with diverse backgrounds
Define and drive the data science vision, strategy, and roadmap, aligning with business and product objectives to improve market competitiveness and rider experience
Provide strong technical guidance and coaching to the team on complex data science problems
Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate insights into decisions and action
Lead deep-dive analyses into large-scale datasets to identify opportunities for improving rider app experience and overall rider product health
Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies
Mentor and guide the professional and technical development of your team members; help develop their careers and assign projects tailored to their skill levels, work styles, and professional goals
Maintain a balance between building sustainable, high-impact projects and shipping quickly
Lead the team in adopting AI-native data science and analytics workflows, embedding AI tooling across data exploration, modeling, and insight delivery
Partner with the Lyft recruiting team to hire high-potential candidates from diverse backgrounds

Experience:

Advanced degree (MS or PhD) in a quantitative field such as Statistics, Applied Mathematics, Economics, Computer Science, or a related area
Hands-on technical experience in experimentation, causal inference, or data science, preferably with applications in machine learning or marketplace dynamics
2+ years of management experience building, leading, and mentoring data science teams
Strong expertise in statistics, experimental design, and causal inference, including A/B testing, multivariate testing, and incremental lift measurement
Strong data storytelling and influence skills, with experience presenting insights and recommendations to senior leaders
Experience launching and monitoring consumer-facing products and iterating through data-driven experimentation and metrics analysis
Experience guiding teams through ambiguous, complex technical challenges to deliver impactful solutions
Experience building or operationalizing machine learning models (e.g., propensity, segmentation, churn, personalization) in partnership with engineering
Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences

Benefits:

Extended health and dental coverage options, along with life insurance and disability benefits
Mental health benefits
Family building benefits
Child care and pet benefits
Access to a Lyft funded Health Care Savings Account
RRSP plan with company match to help save for your future
In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Canada area is CAD $172,000 - CAD 215,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Apply Now

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deep learning engineer jobs in markham, on

Data Science Manager, Rider Experience

Applied Scientist II

Senior AI Engineer

AI Development Engineer - Remote

Generative AI Software Engineer

Principal AI Engineer - AI Engineering & Enablement

Senior ML Engineer

Machine Learning Lead, Edge AI Inferencing

Data Scientist II

Senior AI Engineer - AI Engineering & Enablement

Data Scientist, AI Deployment

Staff AI Engineer

AI Engineering Lead

Senior AI Engineer

Applied Scientist, Sales AI

Applied Scientist, Measurement, Ad Tech, and Data Science (MADS)

Senior Applied Scientist, Measurement, Ad Tech, and Data Science (MADS)

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