Job Description
Are you ready to define the future of intelligent systems? NexaHorizon Technologies is seeking a visionary Senior AI Researcher to lead our groundbreaking Project 2026. In this pivotal role, you will architect the neural frameworks that will underpin the next generation of autonomous agents, pushing the boundaries of what is possible in machine learning and cognitive computing.
As a leader in the AI space, we don't just follow trends; we set them. You will work in a high-performance environment, collaborating with a team of world-class engineers and data scientists to solve complex problems in natural language processing, reinforcement learning, and multimodal synthesis. If you are driven by innovation and want to leave a lasting impact on the industry, this is your opportunity to shine.
Why Join Us?
- Work with cutting-edge hardware and proprietary datasets.
- Competitive compensation package and equity options.
- Flexible remote-first culture with quarterly in-person innovation summits.
- Access to continuous learning budgets and certifications.
Responsibilities
- Design and implement novel deep learning architectures tailored for the Project 2026 roadmap.
- Conduct rigorous research and publish findings in top-tier AI conferences and journals.
- Optimize model inference for low-latency, high-throughput environments.
- Collaborate with cross-functional teams to integrate research models into production systems.
- Identify and mitigate ethical risks and biases in AI model outputs.
- Mentor junior researchers and guide the technical vision of the AI engineering squad.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related quantitative field.
- 5+ years of experience in machine learning research, preferably in a tech-focused industry.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Strong background in Natural Language Processing (NLP) or Computer Vision.
- Proven track record of publishing research papers (e.g., NeurIPS, ICML, ACL).
- Experience with distributed training frameworks (e.g., Ray, MPI).