Job Description
We are at the cusp of a technological revolution, and Nexus Future Labs is leading the charge into 2026. We are seeking a visionary Senior AI/ML Engineer to architect the next generation of artificial intelligence systems. In this role, you will define the roadmap for our proprietary LLMs and predictive algorithms, ensuring we remain at the forefront of the industry. If you are passionate about solving complex problems and building scalable systems for the future, we want to hear from you.
Why Join Us?
- Work on cutting-edge General AI research.
- Competitive compensation and equity package.
- Flexible remote and hybrid work options.
- Access to the latest hardware and cloud resources.
Join us in shaping the future of technology.
Responsibilities
- Architect AI Solutions: Design and implement robust machine learning pipelines and scalable infrastructure for large-scale data processing.
- Model Development: Lead the research and development of advanced Natural Language Processing (NLP) models, specifically focusing on LLM optimization for 2026 standards.
- System Optimization: Improve inference speed and reduce latency for real-time AI applications using distributed computing techniques.
- Team Leadership: Mentor junior engineers and data scientists, conducting code reviews and technical architecture sessions.
- Research Integration: Stay abreast of the latest academic papers and industry trends to integrate novel algorithms into production environments.
- Deployment: Oversee the end-to-end deployment of models to cloud environments (AWS/GCP) ensuring high availability and security.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of professional experience in machine learning engineering or applied research.
- Programming: Expert proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow.
- Cloud Computing: Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Mathematical Proficiency: Solid understanding of linear algebra, calculus, and statistics.
- Problem Solving: Proven track record of solving complex engineering challenges and optimizing system performance.