Job Description
Are you ready to shape the technology landscape of 2026?
Nexus Future Labs is pioneering the next generation of generative intelligence. We are looking for a visionary Senior AI & Machine Learning Engineer to join our elite engineering team in San Francisco. In this role, you won't just be maintaining systems; you will be architecting the core infrastructure that powers the future of human-computer interaction.
As we move into the next era of AI, we need a technical leader who is obsessed with model efficiency, scalability, and ethical AI implementation. You will work directly with our CTO and product leads to deploy state-of-the-art Large Language Models (LLMs) that redefine user experiences.
Why Join Us?
- Impact: Your work will directly influence millions of users globally.
- Future-Proof: Work on cutting-edge technologies expected to dominate the market in 2026 and beyond.
- Equity: Competitive stock option package for early contributors.
Key Areas of Responsibility:
Responsibilities
- Design, train, and deploy scalable machine learning models, specifically focusing on Generative AI and NLP pipelines.
- Optimize existing model architectures for latency and throughput to ensure real-time performance in production environments.
- Collaborate with data scientists and backend engineers to integrate AI models into robust, secure, and scalable web applications.
- Conduct rigorous testing, validation, and monitoring of model performance to ensure high accuracy and reduce hallucinations.
- Stay abreast of the latest research in AI/ML and implement novel techniques to maintain a competitive edge.
- Mentor junior engineers and conduct code reviews to uphold high engineering standards across the team.
Qualifications:
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 5+ years of professional experience in software engineering and machine learning.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of deep learning principles, neural networks, and transformer architectures.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and ability to work in a fast-paced, agile startup environment.