Job Description
Are you ready to engineer the future? 2026 Systems is seeking a visionary Senior AI Engineer to lead our groundbreaking research in autonomous decision-making systems. We are building the infrastructure for the next generation of intelligent agents, and we need a technical mastermind to define our core architecture.
In this pivotal role, you will not just write code; you will shape the trajectory of AI evolution. You will work in a collaborative environment that values innovation, technical excellence, and rapid prototyping. If you are passionate about pushing the boundaries of Large Language Models (LLMs) and reinforcement learning, this is your opportunity to make an indelible mark on the industry.
Why join us?
- Work on cutting-edge projects with a world-class team of engineers and researchers.
- Competitive compensation package including equity.
- Flexible remote-first culture with premium healthcare benefits.
Responsibilities
- Architect and deploy scalable, production-ready machine learning models with a focus on low-latency inference.
- Lead the research and development of next-generation neural network architectures, including Transformers and diffusion models.
- Mentor junior engineers and conduct rigorous code reviews to maintain the highest standards of engineering excellence.
- Collaborate closely with cross-functional teams, including product managers, designers, and hardware engineers, to integrate AI capabilities seamlessly.
- Optimize algorithms for performance, efficiency, and scalability in distributed cloud environments.
- Stay at the forefront of AI research, publishing papers and presenting at top-tier conferences.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 7+ years of professional experience in software engineering and machine learning, with at least 3 years in a senior leadership role.
- Strong proficiency in Python, PyTorch, and TensorFlow.
- Deep understanding of Large Language Models (LLMs), fine-tuning techniques, and RAG pipelines.
- Experience with distributed systems, cloud infrastructure (AWS, GCP, or Azure), and containerization (Docker/Kubernetes).
- Exceptional problem-solving skills and the ability to translate complex business requirements into technical solutions.