Job Description
We are on the precipice of a new era of intelligence. At Nexus Future Technologies, we are building the systems that will define the next decade of human-machine interaction. We are seeking a visionary Senior AI Engineer to join our elite R&D division in San Francisco.
In this role, you won't just maintain legacy systems; you will architect the future. You will lead the development of state-of-the-art Generative AI models, deploying them into production environments that serve millions of users. If you are passionate about pushing the boundaries of Large Language Models (LLMs) and Deep Learning, we want to hear from you.
Join us in shaping the future of technology and earning a competitive compensation package in one of the world's most dynamic tech hubs.
Responsibilities
- Architect Advanced Models: Design, train, and fine-tune complex deep learning architectures, including Transformers and Diffusion models, to solve high-impact business problems.
- Optimize Inference Pipelines: Engineer high-performance inference systems to reduce latency and improve throughput for real-time AI applications.
- Lead Research Initiatives: Conduct cutting-edge research to stay ahead of the curve in the rapidly evolving AI landscape, integrating the latest academic breakthroughs into our products.
- Build Scalable MLOps: Develop and maintain robust CI/CD pipelines for machine learning, ensuring reproducibility, version control, and seamless deployment to cloud infrastructure.
- Collaborate with Cross-Functional Teams: Partner with product managers, data scientists, and engineering teams to translate complex technical requirements into scalable, user-centric solutions.
- Establish Best Practices: Define and enforce coding standards, documentation protocols, and architectural guidelines for the AI engineering team.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent extensive industry experience).
- Technical Proficiency: Expert-level proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Experience: 5+ years of professional experience in AI/ML engineering, with a proven track record of shipping production-grade machine learning systems.
- Cloud & Tools: Strong understanding of cloud platforms (AWS, GCP, or Azure) and MLOps tools (Kubernetes, MLflow, Airflow, DVC).
- NLP/LLM Expertise: Deep knowledge of Natural Language Processing techniques, fine-tuning methodologies, and prompt engineering.
- Communication: Exceptional ability to communicate complex technical concepts to diverse stakeholders, from engineers to executive leadership.