Job Description
Join the Pioneers of the 2026 Vision.
2026 is at the forefront of artificial intelligence, building the infrastructure that will define the next decade of human-computer interaction. We are seeking a world-class Senior Machine Learning Engineer to join our elite team in San Francisco. In this role, you will not just write code; you will architect the future of predictive intelligence.
At 2026, we believe in pushing the boundaries of what is possible. You will work on cutting-edge Large Language Models (LLMs), generative AI, and autonomous systems that impact millions. If you are passionate about solving complex problems and thrive in a high-performance, fast-paced environment, we want to hear from you.
Why Join 2026?
- Impactful Work: Directly influence the roadmap of our flagship AI products.
- Top-Tier Compensation: Competitive base salary plus performance equity.
- World-Class Team: Collaborate with PhDs and industry veterans from top tech firms.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art machine learning models, including Transformers and diffusion models, to solve real-world business problems.
- System Architecture: Design scalable, distributed machine learning infrastructure capable of handling petabyte-scale data processing.
- Research & Innovation: Stay ahead of the curve by exploring emerging AI research (e.g., reinforcement learning, multi-modal AI) and integrating new findings into our production stack.
- Code Quality & Mentorship: Write clean, efficient, and well-documented code; mentor junior engineers and conduct code reviews to maintain high engineering standards.
- Deployment: Oversee the end-to-end MLOps lifecycle, from experiment tracking to production deployment using tools like Kubernetes, MLflow, and AWS SageMaker.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field. A PhD is a plus.
- Experience: 5+ years of professional experience in Machine Learning, Data Science, or a similar role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of deep learning architectures.
- Data Handling: Experience with large-scale data processing (Spark, Hadoop) and data engineering best practices.
- Communication: Excellent verbal and written communication skills, with the ability to translate complex technical concepts for diverse audiences.