AI Team Lead

Description

Remote | Full-Time | Senior Level | Engineering Team

About ScholarshipOwl

ScholarshipOwl is the largest scholarship marketplace in the US, using AI to connect 14 million students who are looking for scholarships with companies that are looking for students. Our mission is to make education financing more accessible and engaging, while giving brands a way to connect with the next generation.

We’re powered by AI technology that simplifies scholarship discovery, streamlines the application process, and delivers measurable results for both students and partners. Whether it’s helping students secure funding or enabling brands to run impactful campaigns, we’re reshaping how education is funded — and discovered.

The Role

We’re looking for a hands-on and strategic AI Team Lead to drive the growth of our AI/ML capabilities. You’ll lead a small, high-impact team focused on building intelligent systems that power everything from personalized scholarship recommendations to AI-enhanced content and search.

You’ll have the opportunity to own the technical roadmap, guide the development of ML pipelines, and explore cutting-edge solutions in LLMs, RAG, Recommender Systems, and Computer Vision. If you're excited about building AI that makes a real-world difference — and mentoring engineers in a fast-paced startup environment — this is the role for you.

What You’ll Do

• Lead and mentor a remote-first team of Machine Learning Engineers

• Architect, develop, and deploy scalable machine learning solutions in production

• Define our AI strategy across use cases like LLMs, search, recommendations, and CV

• Ensure high-quality delivery and best practices across ML lifecycle (data → model → monitoring)

• Collaborate with product, engineering, and sales teams to align AI with company goals

• Stay up to date with the latest research and bring innovative approaches to our stack

• Balance technical hands-on work with leadership, mentorship, and strategic planning

Our Stack

We don’t believe in one-size-fits-all, but here’s what we’re currently using:

• Languages & Frameworks: Python, PyTorch, TensorFlow, Transformers, Scikit-learn, Numpy, Pandas

• ML Ecosystem: HuggingFace, MLflow, Langchain, LLamaIndex

• Vector BDs: Strong preferences for BigQuery and Pinecone

• Cloud Platform: Google Cloud (GCP)

• Workflow & DevOps: Docker, GitLab, CI/CD pipelines, basic MLOps tools

Requirements

• 2+ years in machine learning engineering

• Previous experience as an ML Engineer within an application company, understanding the nuances of integrating ML into end-user products.

• Strong experience with deep learning, ML pipelines, and production deployments

• Hands-on background in one or more of the following:

  • LLMs / RAG systems

  • Computer Vision

  • Recommendation Engines

• Solid understanding of SQL and distributed system fundamentals

• Familiarity with MLOps and cloud-native tools (AWS, Azure, or GCP)

• Clear communicator who thrives in async-first, remote collaboration

• Curious, proactive, and pragmatic — you know when to experiment and when to ship

Benefits

• Mission-Driven Work – Build technology that helps students unlock education opportunities

• Fully Remote – Work from anywhere while collaborating with a global team

• High Impact & Ownership – Small team, big challenges, real autonomy

• Unlimited PTO – Take time when you need it, we trust you

• Coworking Budget – $200/month to invest in your ideal coworking workspace

• Continuous Learning Culture – We support curiosity, experimentation, and growth

• Hardware Budget – Up to $1,600 to invest in your ideal computer.

• Annual Company Off-sites – Meet your teammates in person and connect beyond the screen

Ready to lead and build something meaningful?

Apply now and help us shape the future of AI-powered education.