Machine Learning Engineer

We are looking for a versatile, high-energy Machine Learning Engineer to join our founding team. This isn’t your typical "sit-in-a-corner-and-train-models" role. As an early hire in a fast-paced startup environment, you will bridge the gap between cutting-edge AI research and a polished user product.

The ideal candidate can design a RAG architecture in the morning, fine-tune an LLM in the afternoon, and build the React component to showcase it by evening.

Key Responsibilities

• Generative AI Development: Architect, deploy, and optimize LLM-powered features. This includes prompt engineering, fine-tuning, and agentic system development.

• Full-Stack Integration: Build and maintain the front-end interfaces that bring your AI models to life, ensuring a seamless and responsive user experience.

• End-to-End Pipeline Ownership: Manage the entire ML lifecycle, from data ingestion and preprocessing to model deployment and monitoring in production.

• Documentation & Strategy: Maintain rigorous documentation of model experiments and architectural decisions. You’ll be expected to translate complex technical concepts into clear roadmaps for stakeholders.

• Startup Agility: Wear multiple hats, pivot quickly based on user feedback, and contribute to the product vision beyond just the code.

Qualifications & Skills

• AI/ML - Deep experience with Transformer architectures, PyTorch/TensorFlow, Self-Reflection, and other LLM model improvement methods.

• Front-End - Proficiency in React.js, Next.js, or Vue, along with modern CSS frameworks (Tailwind).

• Engineering - Strong grasp of Python, API design (FastAPI/Flask), and cloud infrastructure (AWS/GCP).

• Soft Skills - Exceptional communication skills; ability to document "the why" and "the how" for a growing team.

• Experience - Startup mindset. You thrive in ambiguity and understand the "move fast and break things" (responsibly) ethos.

Why This Role?

You will have a direct seat at the table, influencing the core product of a lean startup. We value autonomy, candor, innovation, and technical curiosity. If you are tired of being a small cog in a giant corporate machine and want to build the future of Generative AI in HR Tech, let's talk.