Job Description
Join the Future of Intelligence at Nexus Horizon 2026
We are seeking a visionary Senior AI & Machine Learning Engineer to lead our research into next-generation artificial intelligence. As we gear up for the technological landscape of 2026, you will be at the forefront of developing scalable models that redefine human-machine interaction. If you are passionate about pushing the boundaries of what is possible in AI and want to build systems that are not just smart, but ethical and transformative, we want to hear from you.
Why Join Us?
- Work on cutting-edge generative AI and large language models.
- Competitive compensation package and equity options.
- Flexible remote and hybrid work arrangements.
Role Overview
In this pivotal role, you will own the technical strategy for our core AI products. You will design, train, and deploy sophisticated neural networks that power our platform. Your work will directly impact millions of users, optimizing their digital experiences through intelligent automation and predictive analytics.
Responsibilities
- Design, develop, and deploy advanced machine learning models and deep learning architectures.
- Lead the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model training and deployment.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define AI product requirements.
- Optimize existing models for speed, accuracy, and scalability to handle real-time data streams.
- Stay abreast of the latest advancements in AI research and implement state-of-the-art techniques.
- Mentor junior engineers and contribute to the technical vision of the AI department.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Minimum of 5+ years of professional experience in machine learning and AI engineering.
- Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or JAX.
- Proven experience with Natural Language Processing (NLP) and Large Language Models (LLMs).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.