CentML

HQ
Toronto, Ontario, CAN
Total Offices: 2
50 Total Employees
Year Founded: 2022

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Benefits at CentML

Financial + Retirement

401(K)

Company equity

Performance bonus

Office Perks

Commuter benefits

Company-sponsored outings

Free daily meals

Onsite office parking

Relocation assistance

Free snacks and drinks

Health Insurance + Wellness

Dental insurance

Disability insurance

Flexible Spending Account (FSA)

Health insurance

Life insurance

Vision insurance

Mental health benefits

Culture

Flexible work schedule

Open door policy

Open office floor plan

Team based strategic planning

Employee-led culture committees

Day off for your birthday

Quarterly engagement surveys

Hybrid work model

In-person all-hands meetings

Child Care + Parental Leave

Generous parental leave

Vacation + Time Off

Generous PTO

Paid holidays

Paid sick days

Professional Development

Job training & conferences

Mentorship program

Paid industry certifications

Promote from within

Lunch and learns

Personal development training

Apprenticeship programs

Diversity

Hiring practices that promote diversity

Search the 6 jobs at CentML

Recently posted jobs

4 Days Ago
8 Locations
Hybrid
Machine Learning • Software
As a Senior Product Manager, you will lead the strategy and execution of products that optimize AI systems. Your responsibilities include developing a product vision, conducting market research, collaborating with cross-functional teams, defining product requirements, and ensuring successful product delivery, all while engaging with customers to refine features and deliver value.
10 Days Ago
Toronto, ON, CAN
Hybrid
Machine Learning • Software
As a Senior Software Engineer for LLM inference, you will write scalable, high-quality code for backend software, perform benchmarking and profiling for GPU applications, and conduct tests on the inference pipeline while collaborating with diverse teams.
10 Days Ago
Toronto, ON, CAN
Hybrid
Machine Learning • Software
Develop high-performance, power-efficient datacenter solutions for Deep Learning. Optimize GPU kernels, write tests, and benchmarks to evaluate solutions. Communicate with product teams to understand and address performance issues.