Job Description
Shape the Future of Intelligence
Are you ready to define the technological landscape of 2026 and beyond? Nexus Future Labs is seeking a visionary Senior AI/ML Engineer to lead our next-generation generative AI initiatives. We are building the foundational models that will power the autonomous economy of the future, and we need a technical mastermind to turn theoretical breakthroughs into scalable reality.
In this role, you won't just write code; you will architect the brain of our ecosystem. You will work at the intersection of deep learning, distributed systems, and ethical AI, ensuring our solutions are not only powerful but also responsible and transformative.
Why Join Us?
- Work on cutting-edge AGI research in a high-performance environment.
- Competitive compensation package including equity options.
- Flexible remote-first culture with a focus on deep work.
- Access to the latest hardware and cloud infrastructure.
Core Responsibilities
Responsibilities
- Design and implement state-of-the-art deep learning architectures for Large Language Models (LLMs) and Computer Vision applications.
- Optimize model inference latency and throughput to support real-time, high-volume production workloads.
- Conduct original research to pioneer novel algorithms that push the boundaries of current AI capabilities.
- Collaborate with cross-functional teams (Product, Security, Legal) to ensure AI safety, fairness, and compliance with global regulations.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Lead the end-to-end deployment lifecycle of ML models into cloud environments (AWS/GCP/Azure).
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- 7+ years of professional experience in building and deploying production-grade machine learning systems.
- Deep proficiency in Python, PyTorch, or TensorFlow.
- Extensive experience with Transformer architectures, NLP, and generative models.
- Strong background in distributed computing and MLOps practices (Kubernetes, Docker, MLflow).
- Proven track record of leading technical projects from concept to deployment.