Job Description
We are looking for a visionary Senior AI/ML Engineer to lead our next-generation artificial intelligence initiatives. At Nexus Future Tech, we are not just building for today; we are architecting the intelligent systems that will define the landscape of 2026 and beyond. You will be at the forefront of the Generative AI revolution, working with cutting-edge LLMs and neural architectures to solve complex, real-world problems.
Why Join Us?
- Impactful Work: Build AI solutions that scale to millions of users.
- Future-Proof: Work on long-term roadmaps that shape the future of tech.
- Top-Tier Team: Collaborate with world-class researchers and engineers.
If you are passionate about the future of Artificial Intelligence and want to build the foundation for 2026, we want to hear from you.
Responsibilities
- Design, develop, and deploy scalable Machine Learning models and AI pipelines using Python, TensorFlow, and PyTorch.
- Lead the research and implementation of cutting-edge Generative AI techniques, including LLM fine-tuning and RAG architectures.
- Optimize model inference performance to ensure low-latency, high-throughput production environments.
- Collaborate with cross-functional teams (Product, Engineering, Design) to translate business requirements into technical AI solutions.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Stay abreast of the latest academic research and industry trends to drive technological innovation.
- Ensure data privacy, security, and ethical AI practices are integrated into all development cycles.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 5+ years of professional experience in Machine Learning, Deep Learning, or AI engineering.
- Expert proficiency in Python and major ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Strong understanding of Natural Language Processing (NLP) and Large Language Models (LLMs).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of deploying AI models into production environments.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, startup environment.