Job Description
About the Role:
Zenith Systems is pioneering the next generation of adaptive artificial intelligence. We are seeking a visionary Senior 2026 AI Research Scientist to lead our core R&D division. In this pivotal role, you will architect the foundational models that will define the technological landscape of the upcoming decade. You will work at the intersection of deep learning, predictive analytics, and scalable infrastructure, pushing the boundaries of what is possible in 2026.
Why Join Us?
At Zenith, we don't just predict the future; we build it. You will have the autonomy to experiment with cutting-edge technologies, mentor top-tier talent, and directly impact global systems. We offer a competitive benefits package, remote-first flexibility, and a culture of innovation that values bold ideas.
Responsibilities
- Lead Research Initiatives: Define and execute the technical roadmap for 2026-era AI capabilities, focusing on efficiency, scalability, and ethical AI alignment.
- Model Architecture: Design and implement novel neural network architectures capable of processing real-time data streams with zero latency.
- Prototype Development: Build and deploy high-fidelity prototypes for internal testing and client demonstrations.
- Technical Mentorship: Guide a team of junior data scientists and machine learning engineers, conducting code reviews and technical workshops.
- Collaboration: Partner with cross-functional teams including product managers, security experts, and hardware engineers to integrate AI solutions seamlessly.
- Performance Optimization: Continuously refine model inference times and reduce computational costs using advanced quantization and pruning techniques.
- Publication: Author whitepapers and contribute to leading academic conferences in the field of AI.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related field, with a focus on Machine Learning or Artificial Intelligence.
- Experience: Minimum of 7+ years of professional experience in AI research and software development.
- Technical Stack: Proficiency in Python, C++, and TensorFlow or PyTorch. Experience with distributed computing systems (e.g., Kubernetes, AWS, GCP).
- Research Skills: Strong publication record in top-tier venues (NeurIPS, ICML, ICLR) or significant contributions to open-source ML libraries.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems in high-pressure environments.
- Communication: Excellent verbal and written communication skills, capable of translating complex technical concepts for diverse stakeholders.
- Future-Forward Thinking: A deep curiosity regarding emerging technologies and the ability to anticipate industry trends for the year 2026 and beyond.