Job Description
Are you ready to shape the future of artificial intelligence? 2026 Technologies is at the forefront of next-generation neural architecture research, pushing the boundaries of what is possible in machine learning. We are seeking a visionary Senior AI Research Engineer to lead the development of cutting-edge algorithms that will define the industry standards for 2026 and beyond.
In this role, you will not just write code; you will architect the cognitive infrastructure of tomorrow. You will work in a high-performance environment, collaborating with top-tier data scientists and engineers to deploy models that are scalable, efficient, and ethically sound.
Why Join Us?
- Work on groundbreaking projects that redefine the AI landscape.
- Competitive compensation and comprehensive benefits package.
- Access to state-of-the-art hardware and cloud infrastructure.
- A culture of innovation, transparency, and continuous learning.
If you are passionate about the intersection of deep learning and real-world application, we want to hear from you.
Responsibilities
- Lead the architecture and implementation of advanced deep learning models, including transformers and generative AI frameworks.
- Conduct cutting-edge research to improve model accuracy, speed, and energy efficiency for edge and cloud deployment.
- Collaborate with cross-functional teams to translate research into production-ready software solutions.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and knowledge sharing.
- Stay abreast of the latest advancements in AI literature and integrate novel techniques into our engineering pipeline.
- Optimize existing neural networks for low-latency inference in high-traffic environments.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field.
- 5+ years of professional experience in AI/ML engineering, with a proven track record of deploying large-scale models.
- Deep expertise in Python, TensorFlow, PyTorch, or JAX.
- Strong understanding of distributed systems, cloud computing (AWS/GCP/Azure), and MLOps best practices.
- Experience with GPU optimization (CUDA) and hardware acceleration.
- Excellent problem-solving skills and the ability to communicate complex technical concepts clearly.