Job Description
Join the Architects of Tomorrow
Nexus Future Labs is at the forefront of the 2026 technological renaissance. We are seeking a visionary Senior AI & Machine Learning Engineer to lead the development of next-generation generative models and autonomous systems. If you are passionate about pushing the boundaries of what is possible with artificial intelligence, we want to meet you.
As a key member of our elite R&D team, you will be responsible for designing, training, and deploying complex algorithms that will redefine human-computer interaction. You will work in a high-performance environment, collaborating with world-class engineers and data scientists to solve problems that have never been solved before.
Why Join Us?
- Work on cutting-edge projects that shape the future of the tech industry.
- Competitive compensation and equity packages.
- Flexible remote-first policy with premium office amenities in San Francisco.
- Unlimited PTO and continuous learning budget.
Responsibilities
- Design, implement, and optimize deep learning architectures for large-scale NLP and Computer Vision applications.
- Lead the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model deployment and monitoring.
- Collaborate with cross-functional teams to integrate AI models into consumer-facing products and enterprise solutions.
- Conduct rigorous research to stay ahead of the curve in emerging AI methodologies, including LLMs and reinforcement learning.
- Ensure model robustness, scalability, and ethical compliance in all AI implementations.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field, with 5+ years of professional experience in AI/ML.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of Natural Language Processing (NLP) and Large Language Models (LLMs).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of deploying models to production environments.
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.