Job Description
The Opportunity
We are pioneering the next evolution of artificial intelligence, specifically designed to solve complex problems for the year 2026 and beyond. Nexus Future Tech is looking for a visionary Senior AI/ML Engineer to lead our research division. If you are passionate about the intersection of deep learning, generative AI, and ethical architecture, this is your chance to define the future.
Why Join Us?
Work in a high-performance environment focused on scalable, robust AI systems. We offer competitive equity, top-tier health benefits, and the autonomy to experiment with cutting-edge architectures.
Key Responsibilities:
- Architect and implement next-generation neural network models optimized for 2026 computing paradigms.
- Lead the development of robust Large Language Model (LLM) fine-tuning pipelines and RAG (Retrieval-Augmented Generation) systems.
- Collaborate with cross-functional teams to integrate AI solutions into real-world enterprise applications.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Ensure model transparency, fairness, and scalability across distributed cloud environments.
- Conduct rigorous performance benchmarking to ensure low-latency, high-accuracy inference.
Responsibilities
- Architect and implement next-generation neural network models optimized for 2026 computing paradigms.
- Lead the development of robust Large Language Model (LLM) fine-tuning pipelines and RAG (Retrieval-Augmented Generation) systems.
- Collaborate with cross-functional teams to integrate AI solutions into real-world enterprise applications.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Ensure model transparency, fairness, and scalability across distributed cloud environments.
- Conduct rigorous performance benchmarking to ensure low-latency, high-accuracy inference.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field.
- 7+ years of professional experience in Machine Learning, Deep Learning, or AI research.
- Proficiency in Python, PyTorch, and TensorFlow.
- Strong understanding of NLP, Transformers, and generative AI models.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Exceptional problem-solving skills and ability to thrive in a fast-paced, innovative environment.