Job Description
We are on a mission to redefine the boundaries of artificial intelligence. Nexus Innovations is seeking a visionary Lead Generative AI Engineer to spearhead our research and development initiatives for 2026 and beyond. You will be at the forefront of creating adaptive, self-learning systems that integrate seamlessly into enterprise ecosystems.
In this role, you will not just write code; you will architect the future of intelligent automation, ensuring our solutions are scalable, ethical, and transformative. If you are passionate about the next generation of Large Language Models (LLMs) and generative models, we want to hear from you.
Responsibilities
- Design and implement cutting-edge Generative AI models and Large Language Models (LLMs) tailored for enterprise applications.
- Lead the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model training, fine-tuning, and deployment.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical AI solutions.
- Establish and enforce best practices for MLOps, ensuring model reproducibility, version control, and high-performance inference.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning within the technical team.
- Stay abreast of the latest advancements in AI research and integrate novel techniques into our production pipelines.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale AI models to production environments using cloud infrastructure (AWS, GCP, or Azure).
- Strong understanding of transformer architectures, attention mechanisms, and fine-tuning methodologies.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.