Job Description
Join the Vanguard of Artificial Intelligence
Nexus Future Tech is pioneering the next generation of intelligent systems. We are seeking a visionary Senior AI/ML Engineer to architect and deploy scalable machine learning solutions that redefine user experiences. If you are passionate about pushing the boundaries of generative AI, large language models (LLMs), and deep learning, we want to hear from you.
In this role, you will lead critical initiatives that transform raw data into actionable intelligence, working alongside a team of world-class researchers and engineers. We offer a competitive compensation package, equity opportunities, and a culture that fosters innovation and rapid growth.
Why Join Us?
- Work on cutting-edge AI technologies with real-world impact.
- Competitive base salary ($180k - $260k) and equity package.
- Flexible remote-first policy with a hub in the heart of San Francisco.
- Continuous learning budget and access to top-tier tools.
Responsibilities
- Design, train, and fine-tune advanced machine learning models, including LLMs and computer vision systems.
- Build scalable data pipelines and infrastructure to support model training and inference at scale.
- Collaborate with product managers and engineers to translate business requirements into technical AI solutions.
- Optimize existing models for latency, throughput, and accuracy to ensure high performance in production environments.
- Stay abreast of the latest research in AI/ML and integrate novel techniques into our product stack.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
Qualifications
- Master’s or Ph.D. degree in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in machine learning, deep learning, or artificial intelligence.
- Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Deep understanding of NLP, Transformers, or Generative AI architectures.
- Proven track record of deploying models into production environments.