Software Engineer - Quora (Remote)
4h ago⚠️ Before applying, please carefully review all the job requirements
- Location:
- Multiple Locations; Canada; United States
- Work Arrangement:
- Remote
- Job Type:
- Full-time
- Company:
- QUORA
- Salary:
- $97,600 - $139,000 USD + equity + benefits.
- Posted:
- 2026-10-18
- Stack:
- Python, Go, C++, PyTorch, Kubernetes/EKS, NVIDIA Triton, Ray, AWS
Job Overview
- This listing is for a Software Engineer New Grad, Machine Learning Platform - Quora (Remote) position. The role is remote and is classified as full-time. For salary, the listing states rs,. The requirements point towards Python, Docker, AWS, Artificial Intelligence and LLMs. For general context: Artificial intelligence is increasingly part of everyday software products. Large language models power many of today's AI assistants. Interested candidates can review the full details below and apply using the link provided on this page.
What These Requirements Mean in Practice
- ★ Python: Writing readable scripts and backend or data code using Python's standard library and common packages.
- ★ Docker: Packaging an application and its dependencies into containers so it runs the same way everywhere.
- ★ AWS: Using cloud platform services for hosting, storage and databases instead of managing physical servers.
- ★ Artificial Intelligence: A general understanding of how AI systems learn from data, where they are useful, and where they can be unreliable.
- ★ LLMs: Understanding how large language models generate text from prompts, and why their output still needs to be checked.
Skills to Brush Up Before Applying
- ★ Python: core data structures, functions and modules, virtual environments and pip
- ★ Docker: Dockerfile basics, images versus containers, docker compose
- ★ AWS: core compute and storage services, permissions and access control, basic deployment
- ★ Artificial Intelligence: supervised versus unsupervised learning, common real-world use cases, limitations and bias
- ★ LLMs: prompting basics, context limits and hallucinations, using an LLM API
Who May Be a Good Fit for This Role?
- This role may be suitable for candidates who match the skills and experience described in the requirements. Applicants with working knowledge of Python, Docker, AWS, Artificial Intelligence and LLMs may feel well prepared for what the listing describes. A remote arrangement may suit people who work well independently and communicate clearly in writing. This is editorial guidance only, and the employer makes the final decision on suitability.
About The Team And Role
- ★ Https://quoraengineering.quora.com/Migrating-from-x86-to-AWS-Graviton-A-Journey-in-Cost-Optimization-and-Performance
- ★ Https://aws.amazon.com/blogs/containers/quora-3x-faster-machine-learning-25-lower-costs-with-nvidia-triton-on-amazon-eks/
- ★ Https://quoraengineering.quora.com/Building-a-Service-Mesh-in-a-Hybrid-Environment
- ★ Https://quoraengineering.quora.com/Building-Embedding-Search-at-Quora
- ★ Https://quoraengineering.quora.com/Feature-Engineering-at-Quora-with-Alchemy
Application Tips
- Applicants may want to highlight relevant experience with Python, Docker, AWS and Artificial Intelligence in their CV. If you have used AI tools or built small projects with language models, briefly describe what you built and how you checked the results. Keep your CV to the point and tailor the summary to this role rather than sending a generic version. These are general tips, not requirements stated by the employer.
Prepare for Your Interview
- These suggested questions can help you prepare for an interview by focusing on the skills, responsibilities, and technical areas relevant to this role. They are for preparation only and are not confirmed employer questions.
- Q: How do lists, tuples, sets, and dictionaries differ in Python, and when would you use each?
- Q: What problem does Docker solve, and how do an image and a container differ?
- Q: Which cloud services have you used for hosting or storage, and how did you choose them?
- Q: Where could AI add value to a typical web application, and what risks should you plan for?
- Q: How would you explain what a large language model is, and where can its answers be unreliable?
- Q: How do decorators and generators work in Python?
- Q: How would you explain the difference between traditional programming and machine learning to a non-technical person?
- Q: How would you design a prompt and validate the output when using an LLM inside an application?
- Q: How do you stay organised and communicate clearly when working remotely?
Interested Candidates Fill the Application Form: Apply Here