Job Description
We are a pioneer in Advanced Intelligence (AI) and are seeking a visionary Senior AI Engineer to join our elite team. As we scale our operations to redefine the future of technology, you will be instrumental in architecting and deploying next-generation Generative AI solutions. If you are passionate about pushing the boundaries of Machine Learning and want to work in a high-impact environment, we want to hear from you.
Why Join Us?
- Work with state-of-the-art Large Language Models (LLMs).
- Competitive equity package and top-tier benefits.
- Flexible remote-first culture with a collaborative office in SF.
Role Overview:
In this role, you will lead the technical design of our core AI infrastructure, ensuring scalability, efficiency, and ethical deployment of AI models. You will bridge the gap between research and production, working closely with data scientists and product managers to deliver world-class solutions.
Responsibilities
- Architect and Optimize: Design scalable machine learning pipelines and productionize research models with high accuracy and low latency.
- Model Development: Develop, train, and fine-tune Large Language Models (LLMs) for specific enterprise applications.
- Code Review & Mentorship: Lead code reviews, conduct architecture reviews, and mentor junior engineers and data scientists.
- Infrastructure Management: Collaborate with DevOps teams to deploy models on cloud platforms (AWS/GCP) using containerization technologies.
- Performance Tuning: Continuously monitor model performance, conduct A/B testing, and optimize inference costs.
- Research Integration: Stay abreast of the latest advancements in AI research and integrate cutting-edge techniques into our product suite.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years specifically in Generative AI or LLMs.
- Programming: Strong proficiency in Python, PyTorch, or TensorFlow.
- Cloud & Tools: Deep experience with cloud platforms (AWS/GCP), Kubernetes, Docker, and MLOps tools (MLflow, Kubeflow).
- Soft Skills: Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.
- Passion: A deep interest in the ethical implications of AI and a drive to build responsible technology.