Job Description
Are you ready to define the technological landscape for the next decade? OmniFuture Technologies is seeking a visionary Senior AI & Machine Learning Engineer to lead our cutting-edge research division. We are building the foundational models that will power the next generation of intelligent applications, and we need a leader who can bridge the gap between theoretical research and scalable production engineering.
In this role, you won't just maintain legacy systems; you will architect the future. You will work on the bleeding edge of Generative AI, Large Language Models (LLMs), and autonomous agents, ensuring our solutions are not only advanced but also ethical, efficient, and secure.
Why Join Us?
- Work on AI products that impact millions of users globally.
- Competitive compensation package and equity opportunities.
- Access to the latest hardware and compute resources for model training.
- Flexible remote-first culture with a hub in the heart of San Francisco.
Join us in shaping the future of technology for 2026 and beyond.
Responsibilities
- Pioneering the next generation of Generative AI architectures tailored for 2026 scalability and performance.
- Designing and deploying robust Machine Learning pipelines that drive core product innovation and user engagement.
- Collaborating with cross-functional teams to translate complex business requirements into technical AI solutions.
- Optimizing large-scale neural networks for low-latency inference and high-throughput production environments.
- Conducting cutting-edge research in Natural Language Processing (NLP) and Computer Vision.
- Establishing best practices for MLOps, model monitoring, and ethical AI governance.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- Proven experience (5+ years) building and deploying production-grade Deep Learning models.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Strong understanding of distributed systems and cloud infrastructure (AWS, GCP, or Azure).
- Experience with Large Language Models (LLMs) and fine-tuning techniques (e.g., LoRA, PEFT).
- Demonstrated ability to lead technical projects and mentor junior engineers in a fast-paced agile environment.