Software Engineer, Resq
AI focused
Repairs and maintenance marketplace platform for restaurants
Open for applications
Repairs and maintenance marketplace platform for restaurants
101-200 employees
Open for applications
101-200 employees
Company mission
To empower restauranteurs and service providers by delivering the best repair and maintenance experience.
Role
Who you are
- Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degrees are advantageous
- 3-5 years of software development experience, with at least 6 months of professional or personal focus on AI projects involving LLMs
- Strong experience in Python with experience in LLM frameworks or libraries
- Experience with RAG or similar LLM augmentation technologies
- Knowledge of vector databases and efficient data retrieval methods for AI
- Hands-on with multimodal data processing (text, image, video)
- Familiarity with cloud services for AI model deployment (not limited to MLOps)
- Knowledge of tools and platforms that integrate AI for end-user applications
What the job involves
- As a Software Engineer joining ResQ you will be responsible for designing and building the tools and applications that thousands of restaurants and trades businesses across North America use to keep their restaurants and businesses up and running, seamlessly connecting them to a trusted network of vendors
- LLM Development & Integration: Design and implement solutions that use OpenAI & other LLMs for providing value to our users, focusing on accurate information retrieval and generation, live audio capabilities, and more
- Innovation in AI: Explore and implement the latest trends in AI, particularly around multimodal LLMs, agentic RAG systems, and AI-driven search functionalities
- Customization of Models: While not currently on our roadmap, be knowledgeable about techniques to fine-tune LLMs for specific applications, understanding the nuances of model performance in real-world scenarios
- Research & Implementation: Stay up to date with advancements like grounding capabilities, agentic RAG, and multimodal RAG (M3DocRAG), applying these to improve our product offerings
- Performance Optimization: Optimize use AI models audio and text capabilities for efficiency, reducing latency and enhancing scalability in production environments
- Documentation & Knowledge Sharing: Document innovative approaches and share insights with the team to foster a culture of continuous learning
- Troubleshooting: Address and resolve complex issues related to model performance, integration, and data handling
- Mentorship: Support junior developers in learning about LLMs and related technologies
Application process
- Our interview process is done remote utilizing Google Meet
- Stage 1️⃣: Send us your resume and a note about how your story connects to ours. Feel free to focus on what you have learned rather than just a list of responsibilities. Tell us your story! We’ll aim to tell you quickly if it is not the right fit so you are always informed
- Stage 2️⃣: Successful candidates will meet with Amanda, Talent Lead. It will be standardized to keep things fair but also with enough room to show your uniqueness. We’ll communicate the salary range now for full transparency. If you like us and we also think there is a fit, we’ll invite you to the next stage
- Stage 3️⃣: A call with our Co-Founder who will ask you more in depth questions about your experience and skills. Come with questions! If this call goes well and we both want to move forward with each other we will ask you to complete a live coding assignment for your next call
- Stage 4️⃣: This stage will be with our Co-Founder and a member of our engineering team will take you through a systems design interview to get a better understanding of your skills. We will also leave time to give feedback and ask some more questions
- Stage 5️⃣: This stage will be a values interview with a few members of the ResQ team. We will get an understanding of what motivates you and how you work and align to ResQ’s values
- Stage 6️⃣: This is the final stage in the process where you will meet our CEO, KJ. This stage will be more of an introductory call and less focused on your in depth skills and knowledge
Our take
Driving down customer costs is big business anywhere, especially within the world of restaurants which already have razor-thin margins and built-in volatility. ResQ's service acts as “revenue recovery” for its customers by connecting maintenance contractors to restaurants and providing them with one spot to organize communication, pay bills and establish accountability, saving worker time and offering clearer visualization into how repairs will work.
ResQ's customers include 4,000 leading restaurants such as KFC, Taco Bell and Pizza Hut. According to the company, restaurants benefit from ResQ's platform by decreasing annual revenue costs by as much as 20%. In 2021, the company was valued at $25.81 billion.
The company is expecting to continue growing its team across engineering, sales and operation roles. ResQ is also earmarking money for launches in new markets.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Oct 2021
$39m
SERIES A
Jun 2021
$7.5m
SEED
Total funding: $48m
Company benefits
- Comprehensive Health Plans
- Roam Away from Home
- Unlimited Time Off
- Wellness Platform
- Quarterly Company Outings
- Monthly Team Events
- Parental Leave
Company values
- Take Extreme Ownership
- Deliver WOW Experiences
- Uplift & Inspire
- Keep it Real
Company HQ
Downtown Yonge East, Toronto, ON
Articles
Leadership
Kuljeev Singh
(CEO & Founder)Experience as Venture Capitalist for iGan Partners for 7 years, and owner of Kanga Pies restaurant for 5 years.
Salary benchmarks
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