Job Description
We are building the infrastructure for tomorrow. Nexus Future Labs is currently seeking a visionary Senior AI Engineer to join the elite team working on Project 2026, our proprietary generative AI platform designed to redefine human-machine interaction in the enterprise sector.
In this role, you will not just write code; you will architect the neural pathways of the future. We are looking for a self-starter who thrives in ambiguity and possesses the technical prowess to solve complex, large-scale machine learning problems. If you are passionate about pushing the boundaries of what is possible in AI and want to be part of a mission-driven organization, we invite you to apply.
Why Join Us?
- Work on bleeding-edge technology with a team of industry leaders.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium benefits.
- Access to state-of-the-art computing resources and research.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale Transformer models using Python and PyTorch.
- Optimization: Implement advanced optimization techniques to reduce inference latency and improve model efficiency.
- System Architecture: Build scalable MLOps pipelines for continuous integration and deployment of AI models.
- Research: Stay abreast of the latest academic research in NLP and Deep Learning to apply novel architectures to Project 2026.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate business requirements into technical solutions.
- Code Review & Mentorship: Lead code reviews and mentor junior engineers to foster a culture of technical excellence.
Qualifications
- Education: Master’s degree or Ph.D. in Computer Science, Mathematics, or a related field.
- Experience: Minimum of 5 years of professional experience in Machine Learning Engineering or Applied AI.
- Technical Skills: Expert proficiency in Python, PyTorch, TensorFlow, and SQL.
- Cloud Expertise: Strong experience deploying models on AWS, GCP, or Azure using containerization tools like Docker and Kubernetes.
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Large Language Models (LLMs), or Generative AI.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.