Job Description
Are you ready to build the technological foundations of tomorrow? Nexus Future Labs is seeking a visionary Senior AI/ML Architect to join our elite research division. As we prepare for the AGI era, we need a master of neural networks who can architect scalable, ethical, and groundbreaking systems.
In this role, you won't just use existing tools; you will help define the standards for 2026 and beyond. You will lead the development of next-generation generative models, optimize large-scale inference pipelines, and collaborate with a team of world-class researchers to push the boundaries of Artificial Intelligence.
If you are passionate about the future of technology and want to leave a lasting legacy in the AI space, apply today.
Responsibilities
- Architect and deploy state-of-the-art Large Language Models (LLMs) and multimodal systems optimized for the 2026 tech stack.
- Design scalable machine learning infrastructure on cloud platforms (AWS/GCP/Azure) to handle high-throughput data processing.
- Conduct cutting-edge research in Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- Optimize model inference latency and cost-efficiency to support real-time applications.
- Establish ethical AI guidelines and bias mitigation strategies for future-ready algorithms.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Stay ahead of industry trends to integrate emerging technologies (e.g., Neuromorphic Computing) into our roadmap.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field (PhD preferred).
- 8+ years of experience in Machine Learning, Deep Learning, or Artificial Intelligence engineering.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying models to production at scale (e.g., Kubernetes, Docker, Terraform).
- Deep understanding of transformer architectures, attention mechanisms, and vector databases.
- Strong experience with MLOps pipelines, data versioning, and experiment tracking (MLflow, Weights & Biases).
- Excellent problem-solving skills and the ability to thrive in a fast-paced, high-stakes environment.