Job Description
At 2026, we are not just predicting the future; we are architecting it. We are a team of visionaries and technologists dedicated to building the world's most advanced artificial intelligence systems. We are looking for a Senior AI Engineer to join our elite R&D division in San Francisco and help shape the trajectory of machine learning for the next decade.
In this role, you will be at the forefront of innovation, working with cutting-edge Large Language Models (LLMs) and generative AI technologies. You will collaborate with world-class researchers and product engineers to deploy scalable, efficient, and ethical AI solutions that impact millions of users globally. If you are passionate about pushing the boundaries of what is possible in AI and thrive in a fast-paced, high-impact environment, we want to hear from you.
Why Join Us?
- Work on next-generation AI infrastructure.
- Competitive compensation and equity packages.
- Unlimited PTO and a fully remote-first culture with a premium SF office.
- Access to the latest hardware and cloud resources.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art Large Language Models (LLMs) and transformer architectures to improve performance and accuracy.
- Research Implementation: Translate theoretical research papers into production-ready code and deploy them on scalable cloud infrastructure.
- System Optimization: Optimize inference pipelines and reduce latency for real-time AI applications using techniques like quantization and model distillation.
- Cross-Functional Collaboration: Partner with product managers, designers, and software engineers to define AI requirements and deliver intuitive user experiences.
- Code Review & Mentorship: Lead code reviews, conduct technical architecture discussions, and mentor junior engineers and data scientists.
- Ethical AI: Ensure AI systems are fair, transparent, and adhere to safety guidelines and ethical standards.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of deep learning fundamentals.
- Experience: 5+ years of experience in machine learning engineering or applied research, preferably in a high-scale production environment.
- LLM Expertise: Hands-on experience with LLM training, fine-tuning (PEFT/LoRA), and evaluation metrics (e.g., BLEU, ROUGE, HumanEval).
- Cloud Skills: Experience deploying models on AWS, GCP, or Azure using containerization (Docker/Kubernetes).
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.