Job Description
We are building the future of intelligent automation, and we need a visionary Senior AI Engineer to lead our Generative AI initiatives. As we look toward 2026 and beyond, our mission is to integrate advanced LLMs into enterprise workflows, creating seamless, human-like interactions.
In this role, you won't just write code; you will architect the brain of our next-generation platform. You will work at the intersection of research and production, pushing the boundaries of what is possible with Large Language Models and multimodal AI systems. If you are passionate about building scalable AI infrastructure and solving complex problems with code, we want to meet you.
Why Join Us?
- Work with state-of-the-art technology stacks including PyTorch, Hugging Face, and custom GPU clusters.
- Competitive compensation package with equity opportunities.
- Flexible remote-first culture with a presence in the heart of San Francisco.
Responsibilities
- Design, train, and fine-tune large-scale language models (LLMs) and generative AI models tailored for specific business domains.
- Deploy and optimize AI models for low-latency, high-throughput inference using cloud infrastructure (AWS/GCP).
- Collaborate with product managers and data scientists to define AI requirements and translate them into technical specifications.
- Implement robust evaluation frameworks and A/B testing strategies to measure model performance and user engagement.
- Mentor junior engineers and contribute to the technical vision of the AI research team.
- Stay ahead of the curve by researching emerging trends in AI, NLP, and prompt engineering.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- 5+ years of professional experience in software engineering, with at least 3 years specifically focused on Machine Learning or AI.
- Deep understanding of NLP concepts, including Transformers, BERT, GPT architectures, and RAG (Retrieval-Augmented Generation).
- Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Experience with model deployment tools such as Kubernetes, Docker, and MLflow.
- Strong problem-solving skills and ability to work in a fast-paced, agile environment.