Machine Learning Engineer, New Grad - Quora

Overview

This opportunity is for a partner company, which handles applications and the rest of the hiring process directly. The employer is seeking a new graduate Machine Learning Engineer for Quora, based in the United States.

You will join a product engineering team focused on AI-driven consumer experiences that reach millions of users around the world. The role centers on modern machine learning work, including large language models and generative AI use cases, with an emphasis on building systems that are ready for production.

This is a remote-first position where you will work closely with engineers, product stakeholders, and other cross-functional partners. It is a strong fit for an early-career candidate who is excited about AI, machine learning, and creating technology that helps people discover and exchange knowledge.

The position gives you ownership of meaningful work while continuing to learn from experienced technical teammates in a collaborative environment.

What you'll do

• Develop and improve user-facing AI features that use large language models and generative AI tools.
• Work across the AI stack, including prompt design, agent-based workflows, model assessment, and tuning.
• Plan and execute structured testing such as A/B experiments and offline evaluations to track changes in engagement, quality, and trust.
• Work with product and engineering partners to turn user needs into scalable machine learning solutions.
• Strengthen the reliability of AI systems through monitoring, quality reviews, guardrails, and root-cause analysis of failures.
• Improve production AI systems for speed, cost, latency, and scale.
• Help maintain a culture of strong technical standards, experimentation, ongoing learning, and knowledge sharing.

What we're looking for

• Currently pursuing or recently finished a B.S., M.S., or Ph.D. in Computer Science, Engineering, or a related technical discipline, with graduation expected in 2025 or 2026.
• Solid grasp of the mathematical principles behind machine learning methods.
• Hands-on exposure to LLM applications, transformer-based models, or similar AI technologies.
• Comfort coding in Python or C++, or the ability to pick up new languages quickly.
• Strong written English skills, with the ability to judge tone, accuracy, clarity, and subtle meaning in text.
• Genuine interest in learning, experimentation, and ongoing improvement.
• Ability to work effectively with engineering and product teams in a remote setting.
• Availability to collaborate during required coordination hours: Monday to Friday, 9 AM to 3 PM Pacific Time.
• Prior software engineering exposure through internships, professional roles, or coding competitions is a plus.
• Experience building AI agents or machine learning systems at production scale is an advantage.

Compensation and benefits

The company offers a competitive salary that varies by location, experience, education, and business needs.

For Canadian locations, the listed compensation ranges are:

• Toronto and Vancouver: CA$137,852 to CA$157,061, plus equity and benefits.
• Other Canadian locations: CA$128,661 to CA$146,590, plus equity and benefits.

• Equity opportunities, with possible refresh grants.
• Comprehensive medical, dental, and vision coverage.
• Remote-first setup with reimbursement for remote work expenses.
• Paid time off and employee assistance programs.
• The chance to contribute to high-impact AI and machine learning work at global scale.
• A supportive and inclusive environment that values collaboration, innovation, and continuous learning.

Application and hiring notes

This posting is managed through a partner company’s hiring process. The partner reviews applications and handles the next steps, while the final decision, interviews, and assessments are managed by the hiring company’s internal team.

The application process may use AI-assisted tools to help review resumes, analyze responses, and flag possible inconsistencies or verification signals. These tools support the recruitment team, but human judgment remains the basis for final hiring decisions.

By applying, candidates acknowledge that their personal data may be processed for candidate evaluation and shared with the hiring employer under applicable data protection rules, including GDPR where relevant. Applicants may request access, correction, deletion, objection, and other rights under applicable law.