About this role
TechWolf is at the forefront of transforming the HR tech industry through the power of Artificial Intelligence. Our AI team owns everything from cutting-edge research through end-to-end production deployment, empowering companies to thrive in the age of AI through skills-based decision making. We prioritize fair, transparent, and impactful AI.
As a Junior AI Engineer, you'll learn how to turn an idea into an AI feature that customers use every day. Our AI team works close to the product and close to our customers: we experiment quickly, measure carefully and ship what works. Here's what you can expect: Hands-On Learning: You'll learn from experienced AI engineers through mentorship, pairing sessions and code reviews, and build a real understanding of how AI systems work in production. Real Product Impact: Your work reaches customers. Within your first months you'll ship features that enterprises rely on. Room to Experiment: New models and techniques appear every week. We give you the space to try them, measure them and share what you find. Career Growth: We're invested in your success. As your strengths and interests become clear, we'll tailor a development plan to help you grow into a well-rounded AI engineer.
What you'll do
- Model Development: Help improve the models and pipelines that infer skills from the work people actually do, using Transformers, PyTorch and LLMs, and measure whether each change makes our inference more accurate.
- Agent Engineering: Help build agentic features with LLMs (AWS Bedrock) and modern agent SDKs, from first prototype to production.
- Evaluation: Build eval sets and offline evaluations that show whether a change actually makes a feature better, and learn to read the signals from production.
- Experimentation: Try new models, prompts and approaches, and share what you learn, including what didn't work.
- Productization: Ship your work as tested, observable Python services (FastAPI, Docker, Kubernetes) in AWS.
- Product & Customer Focus: Work with Product and customer-facing colleagues to understand the problem before building the solution.