Job Description
At 2026, we are not just building software; we are architecting the future of intelligence. We are seeking a visionary Senior AI Engineer to join our elite team in San Francisco and help define the technological landscape of the coming decade. You will be at the forefront of developing next-generation neural architectures and scalable machine learning systems that power our global platform.
We are looking for someone who thrives in ambiguity and has a passion for pushing the boundaries of what is possible with Artificial Intelligence. If you want to build systems that matter and work at the intersection of advanced algorithms and real-world impact, this is your opportunity.
Why join us?
- Work on cutting-edge AI projects that redefine industry standards.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a vibrant SF office.
Responsibilities
- Architect & Develop: Design, implement, and deploy state-of-the-art machine learning models and deep learning frameworks using Python, TensorFlow, and PyTorch.
- System Optimization: Optimize large-scale data pipelines and model inference to ensure high performance, low latency, and cost-efficiency.
- Research & Innovation: Conduct in-depth research to explore novel AI techniques, including Generative AI, NLP, and Computer Vision.
- Mentorship: Lead and mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Collaboration: Partner with cross-functional teams (Product, Engineering, Design) to translate complex business requirements into robust AI solutions.
- Production Deployment: Manage the full lifecycle of ML models from experimentation to production deployment on cloud infrastructure.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field; PhD preferred.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or AI Engineering.
- Technical Skills: Proficiency in Python, C++, or Java; strong experience with PyTorch or TensorFlow.
- Frameworks: Deep understanding of MLOps, Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).
- Algorithms: Solid grasp of statistical analysis, optimization techniques, and algorithm design.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.