Job Description
We are pioneering the Project 2026 initiative, a cutting-edge research initiative aimed at revolutionizing generative AI capabilities. We are seeking a visionary Lead Machine Learning Engineer to join our elite team in San Francisco and help architect the neural networks of tomorrow.
In this role, you will not just write code; you will define the future of intelligent systems. You will work with world-class researchers and engineers to build scalable, efficient, and ethical AI models that will set the standard for the industry. If you are passionate about pushing the boundaries of what is possible in machine learning, this is your opportunity to leave a lasting legacy.
Why Join Us?
- Work on Project 2026, a top-tier initiative funded by leading tech visionaries.
- Competitive compensation package including equity and health benefits.
- Flexible remote-first culture with a vibrant office in downtown San Francisco.
- Access to the latest hardware and computational resources.
Responsibilities
- Architect and implement scalable machine learning pipelines and infrastructure using Python, TensorFlow, and PyTorch.
- Lead a team of junior and senior engineers to deliver high-quality, production-ready models for the 2026 initiative.
- Optimize deep learning models for speed, accuracy, and resource efficiency on massive datasets.
- Collaborate with cross-functional teams, including data scientists and product managers, to define technical requirements.
- Conduct rigorous code reviews and mentorship to ensure engineering excellence across the organization.
- Stay ahead of the curve on the latest research in AI and apply novel techniques to our core products.
Qualifications
- PhD or Master's degree in Computer Science, Machine Learning, or a related quantitative field.
- Minimum of 8 years of professional experience in software engineering and machine learning.
- Proven experience leading technical teams and managing complex projects.
- Deep expertise in deep learning frameworks (TensorFlow, PyTorch, JAX) and distributed computing.
- Strong proficiency in Python, SQL, and cloud platforms (AWS, GCP, or Azure).
- Exceptional problem-solving skills and a track record of shipping innovative AI solutions.