Job Description
Are you ready to architect the intelligent systems of tomorrow? Nexus Future Labs is seeking a visionary Senior AI/ML Architect to lead our next-generation research initiatives. In this pivotal role, you will define the technical roadmap for our proprietary generative AI platforms, ensuring our solutions are scalable, ethical, and at the forefront of industry innovation.
We are not just building software; we are shaping the future of human-machine interaction. You will work alongside world-class researchers and engineers to solve complex problems in natural language processing, computer vision, and predictive analytics. If you have a passion for pushing the boundaries of what is possible in 2026 and beyond, we want to hear from you.
Why Join Nexus Future Labs?
- Impactful Work: Directly influence the architecture of products used by millions.
- Future-Ready: Work on cutting-edge technologies that define the next decade.
- Competitive Compensation: Top-tier salary and equity package.
Responsibilities
- Design and implement scalable machine learning infrastructure and MLOps pipelines to support large-scale model training and deployment.
- Lead the architecture of complex AI systems, ensuring high performance, reliability, and security standards are met.
- Collaborate with cross-functional teams (Data Science, Product, Engineering) to translate business requirements into technical solutions.
- Research and prototype novel algorithms to improve model accuracy and efficiency.
- Establish best practices for data governance, model monitoring, and ethical AI usage.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field, or equivalent practical experience.
- 7+ years of professional experience in machine learning, AI, or data science.
- Deep expertise in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Strong understanding of distributed systems and cloud architecture (AWS, GCP, or Azure).
- Experience with NLP and Large Language Models (LLMs) is highly preferred.
- Proven track record of shipping production-level AI applications.
- Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.