Job Description
Are you ready to engineer the future of Artificial Intelligence? Nexus Future Labs is seeking a visionary Senior AI & Machine Learning Engineer to lead our cutting-edge research division. In this role, you will not just use existing tools; you will architect the foundational models that will define the industry in 2026 and beyond. We are looking for a problem solver who thrives in ambiguity and is passionate about scaling intelligent systems to solve complex global challenges.
As a key member of our technical leadership team, you will bridge the gap between theoretical research and production-grade deployment. We offer a competitive compensation package, equity packages, and an environment that fosters innovation and creativity.
Responsibilities
- Architect and deploy scalable machine learning pipelines capable of handling petabyte-scale data streams.
- Lead the research and development of proprietary Large Language Models (LLMs) and autonomous AI agents.
- Collaborate closely with product managers and engineers to integrate AI solutions into high-impact consumer applications.
- Optimize model inference latency and accuracy to ensure seamless, real-time user experiences.
- Mentor junior engineers and establish rigorous best practices for data governance, model training, and MLOps.
- Explore and prototype emerging technologies, including quantum computing interfaces and edge AI paradigms.
- Present technical strategies and research findings to executive stakeholders and the wider engineering community.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- 8+ years of professional experience in Machine Learning, Deep Learning, or Artificial Intelligence.
- Proficiency in Python, PyTorch, TensorFlow, and modern GPU acceleration frameworks (CUDA).
- Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning architectures.
- Strong experience with MLOps tools such as Kubernetes, Docker, and MLflow for model lifecycle management.
- Demonstrated ability to translate complex business requirements into scalable, efficient engineering solutions.
- Excellent communication skills with the ability to articulate technical concepts to non-technical stakeholders.