Job Description
Shape the Future of Artificial Intelligence
Are you ready to pioneer the next generation of intelligent systems? Zenith Future Systems is seeking a visionary Senior AI Research Engineer to lead our breakthrough initiatives in Agentic AI and Generative Models. We are building the technology stack for the year 2026 and beyond, and we need a technical expert to define the roadmap.
Why Join Us?
At Zenith, we don't just follow trends; we set them. You will work in a cutting-edge R&D environment with access to the latest compute infrastructure, collaborate with top-tier researchers, and have a direct impact on how the world interacts with AI. We offer competitive compensation, equity packages, and a flexible remote-first culture.
Key Responsibilities
- Architect and train large-scale foundation models and generative AI systems designed for the enterprise of tomorrow.
- Drive the research and development of novel algorithms to improve model efficiency, accuracy, and scalability.
- Collaborate with cross-functional engineering teams to deploy research models into production environments.
- Conduct rigorous testing and validation to ensure safety, ethics, and compliance in AI outputs.
- Publish high-impact research papers and present findings at top-tier industry conferences.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, or a related technical field.
- Minimum of 5 years of experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of implementing state-of-the-art models such as Transformers, LLMs, or Diffusion models.
- Experience with MLOps, model serving, and cloud infrastructure (AWS, GCP, or Azure).
Skills
Python, PyTorch, TensorFlow, Natural Language Processing, Large Language Models, MLOps, Deep Learning, AI Research
Responsibilities
- Architect and train large-scale foundation models and generative AI systems designed for the enterprise of tomorrow.
- Drive the research and development of novel algorithms to improve model efficiency, accuracy, and scalability.
- Collaborate with cross-functional engineering teams to deploy research models into production environments.
- Conduct rigorous testing and validation to ensure safety, ethics, and compliance in AI outputs.
- Publish high-impact research papers and present findings at top-tier industry conferences.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, or a related technical field.
- Minimum of 5 years of experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of implementing state-of-the-art models such as Transformers, LLMs, or Diffusion models.
- Experience with MLOps, model serving, and cloud infrastructure (AWS, GCP, or Azure).