Job Description
We are 2026 Systems, a pioneering technology firm dedicated to shaping the future of artificial intelligence and automation. As we look toward the technological landscape of 2026 and beyond, we are seeking a visionary Senior AI Engineer to lead our advanced research and development initiatives.
In this role, you will be at the forefront of innovation, working on cutting-edge projects that define the next generation of intelligent systems. You will collaborate with a diverse team of world-class engineers, data scientists, and product strategists to build scalable, robust, and ethical AI solutions.
Why Join Us?
- Work on mission-critical AI infrastructure for a Fortune 500 client.
- Competitive compensation package and equity options.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to influence the roadmap for 2026 and beyond.
If you are passionate about the future of technology and want to make a tangible impact, we want to hear from you.
Responsibilities
- Design, develop, and deploy scalable machine learning models and neural networks.
- Optimize existing AI pipelines to improve inference speed and reduce latency.
- Conduct research on emerging AI architectures to stay ahead of industry trends.
- Collaborate with cross-functional teams to integrate AI solutions into production environments.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning.
- Evaluate and select appropriate AI frameworks and tools (e.g., PyTorch, TensorFlow).
- Ensure all models adhere to ethical guidelines and regulatory standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
- 5+ years of professional experience in machine learning and deep learning.
- Strong proficiency in Python, C++, and SQL.
- Proven experience with large language models (LLMs) and generative AI technologies.
- Deep understanding of distributed systems and cloud platforms (AWS/GCP/Azure).
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.
- Experience with MLOps and model deployment strategies.