Remote | Full-Time | Senior Level | Engineering Team
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.
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.
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
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
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
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.
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