Job Description
We are on a mission to architect the next generation of artificial intelligence. As a Senior AI & Machine Learning Engineer, you will lead the development of proprietary models designed to operate seamlessly in the dynamic landscape of 2026 and beyond. We are looking for a visionary technologist who is not just proficient in current stack technologies but is also capable of anticipating the paradigm shifts in Generative AI, Autonomous Systems, and Ethical Machine Learning.
Why Join Us?
- Future-Ready Tech Stack: Work with cutting-edge tools including PyTorch, TensorFlow, and next-gen LLM frameworks.
- Impactful Work: Your algorithms will power solutions that redefine human-computer interaction.
- Competitive Compensation: A market-leading salary package plus equity options.
- Flexible Environment: Hybrid work model based in the heart of San Francisco's tech district.
If you are passionate about pushing the boundaries of what is possible with AI, we want to hear from you.
Responsibilities
- Architect & Implement: Design and deploy scalable deep learning architectures for large-scale production environments.
- R&D Leadership: Drive research initiatives focused on multimodal AI, reinforcement learning, and edge computing optimization.
- Model Optimization: Improve model latency, accuracy, and resource efficiency to meet enterprise-grade standards.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Strategic Planning: Contribute to the technical roadmap, identifying emerging trends to ensure the company remains ahead of the curve.
- Collaboration: Partner with product managers and engineers to translate complex research into practical, user-centric applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 7+ years of professional experience in AI/ML, Machine Learning Engineering, or Data Science.
- Technical Skills: Deep expertise in Python, C++, and frameworks such as PyTorch, TensorFlow, or JAX.
- Domain Knowledge: Proven track record in Natural Language Processing (NLP), Computer Vision, or Generative AI.
- Problem Solving: Strong analytical skills with the ability to troubleshoot complex algorithms and data structures.
- Communication: Excellent written and verbal communication skills, capable of presenting technical concepts to non-technical stakeholders.