Job Description
Are you ready to architect the future of intelligence?
Nexus AI Labs is seeking a visionary Senior AI Engineer to join our elite team in San Francisco. We are building the next generation of generative AI systems that will redefine human-computer interaction. In this role, you will be at the forefront of technological innovation, designing and deploying scalable machine learning models that solve complex real-world problems.
You will work with state-of-the-art hardware and proprietary datasets to train, fine-tune, and optimize large language models and neural networks. If you are passionate about pushing the boundaries of AI and want to build products that have a global impact, we want to hear from you.
Why Join Nexus AI Labs?
- Impactful Work: Directly contribute to the development of AI systems used by millions.
- Top-Tier Compensation: Competitive salary ($180k - $260k) and equity package.
- Modern Culture: Flexible remote work, unlimited PTO, and a focus on continuous learning.
- Resources: Access to the latest research papers, compute clusters, and mentorship from industry experts.
Responsibilities
- Architect and deploy scalable machine learning models into production environments using Kubernetes and cloud infrastructure.
- Lead research initiatives in Natural Language Processing (NLP) and Deep Learning, focusing on fine-tuning and RAG (Retrieval-Augmented Generation).
- Optimize data pipelines for high-throughput training and inference, ensuring low latency and high accuracy.
- Collaborate with cross-functional product and engineering teams to translate complex business requirements into robust technical solutions.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
- Stay abreast of the latest advancements in AI research (e.g., Transformer architectures, Diffusion models) and integrate them into our stack.
Qualifications
- PhD or Master’s degree in Computer Science, Statistics, Mathematics, or a related technical field.
- Minimum of 5 years of professional experience in AI/ML engineering, with a focus on large language models.
- Strong proficiency in Python, PyTorch, or TensorFlow, with deep understanding of deep learning frameworks.
- Proven experience implementing MLOps practices, CI/CD pipelines, and model monitoring.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to thrive in a fast-paced, agile startup environment.