Founding Engineer, AI

GuruLink; Toronto; Remote; CAD 80,000 - 150,000; Full time

Job summary

An innovative startup is seeking a skilled AI expert to lead the development of a groundbreaking generative AI system. This role offers a unique opportunity to shape a product from inception, focusing on data pipeline optimization and dataset creation. You will engage in hands-on coding, manage a talented engineering team, and tackle complex data challenges. Join a forward-thinking company that values experimentation and innovation, while enjoying the flexibility of remote work across Canada. If you're passionate about AI and eager to make a significant impact, this is the perfect opportunity for you!

Benefits

Significant equity stake

Remote work flexibility

Innovative AI product development

Startup environment

Collaboration with sales team

Qualifications

• Experience with zero-to-one startups and enterprise software.
• Proficiency in AI coding tools and managing large datasets.

Responsibilities

• Define technical architecture and manage an initial team of engineers.
• Analyze and clean large datasets for AI applications.

Skills

AI coding tools

Data management

Vector databases

Data annotation techniques

Cloud platforms

RAG pipelines

Startup experience

Tools

Pinecone

Weaviate

FAISS

Docker

Kubernetes

Job description

Location: REMOTE / Toronto, Ontario
This job allows you to work remotely.

Are you ready to dive into the world of cutting-edge AI technologies? A remarkable opportunity awaits you to lead the development of a groundbreaking system designed to enhance the accuracy of generative AI applications for contact centers. As an experienced AI expert, you will have the chance to shape a product that has never been built before, leveraging your skills to optimize data pipelines and create high-quality datasets.

What You'll Be Doing:

1. Define the entire technical architecture for the solution.
2. Develop and refine processes for cleaning, curating, labeling, and securing datasets for AI bots.
3. Engage in hands-on coding to bring the vision to life.
4. Recruit, hire, and manage an initial team of talented engineers.
5. Cultivate a culture focused on testing and measuring the effectiveness of new methods.
6. Manage a development budget of $1M annually.
7. Innovate through experimentation, solving complex data challenges using human feedback.

Challenges You'll Tackle:

1. Analyze large, complex unstructured datasets to identify conflicts, duplicates, and missing data.
2. Determine optimal strategies for data cleaning and enrichment.
3. Label unannotated data and establish a set of gold standard answers.
4. Integrate third-party evaluation frameworks to demonstrate data improvement.
5. Maintain a clean and ready-to-use dataset for generative AI applications.

Success Metrics:

1. Utilize third-party evaluation tools to showcase clear performance enhancements.

Potential Scope:

1. Design and optimize RAG pipelines for the client's AI application.
2. Integrate vector search engines like Pinecone, Weaviate, or FAISS for efficient document retrieval.
3. Define metrics and KPIs to measure pipeline accuracy and efficiency.
4. Document processes for team knowledge sharing.
5. Engage in social media for marketing purposes.
6. Collaborate with the sales team.

What's In It For You?

1. Join a startup at its inception, led by a serial founder.
2. Receive a significant equity stake.
3. Work remotely from anywhere within Canada.
4. Contribute to innovative AI products and technologies.

Must Have Skills:

What You've Done:

1. Experience with zero-to-one startups.
2. Background in enterprise software and data.
3. Proficiency in AI coding tools.
4. Expertise in vector databases and retrieval tools.
5. Familiarity with data annotation tools and techniques.
6. Experience building and deploying RAG pipelines or similar systems.
7. Ability to manage large datasets for training and evaluation.
8. Skilled in deploying models and pipelines at scale using cloud platforms or containerized environments.
9. Previous involvement in SR&ED processes and documenting projects to align with SR&ED funding requirements.

Tech Stack You'll Be Working With:

1. Vector search engines like Pinecone, Weaviate, FAISS.
2. Cloud platforms and containerization tools (e.g., Docker, Kubernetes).
3. Data annotation and evaluation frameworks.