Job Description
Are you ready to architect the future of artificial intelligence? OmniFuture Technologies is leading the charge on Project 2026, a revolutionary initiative aimed at defining the next generation of autonomous systems and generative AI agents. We are seeking a visionary Senior AI Architect to join our elite engineering team and build the foundational models that will power the digital landscape of the future.
In this role, you won't just write code; you will define the paradigm of machine learning for the coming decade. You will work in a high-performance environment with top-tier researchers and engineers, pushing the boundaries of what is possible in NLP, Computer Vision, and Reinforcement Learning.
Why Join Us?
- Impact: Directly influence the roadmap for 2026 and beyond.
- Compensation: Competitive salary and equity package.
- Flexibility: Hybrid work model in the heart of San Francisco.
- Technology: Access to cutting-edge hardware and cloud infrastructure.
If you are passionate about building scalable, efficient, and ethical AI systems, we want to hear from you.
Responsibilities
- Design and implement scalable AI/ML architectures for Project 2026, focusing on large language models (LLMs) and multi-agent systems.
- Lead the end-to-end development lifecycle of machine learning models, from data ingestion to model deployment in production environments.
- Optimize neural network performance for speed and accuracy, utilizing techniques such as quantization, pruning, and distributed training.
- Collaborate with cross-functional teams including data scientists, product managers, and security experts to ensure robust, compliant AI solutions.
- Stay at the forefront of AI research, evaluating and integrating new methodologies (e.g., Transformers, Diffusion Models) into our core stack.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards across the organization.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
- Minimum of 5+ years of professional experience in designing and deploying machine learning systems at scale.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of Natural Language Processing (NLP) and Large Language Model (LLM) architectures (e.g., GPT, BERT).
- Experience with MLOps tools such as Docker, Kubernetes, MLflow, and cloud platforms (AWS/GCP/Azure).
- Strong problem-solving skills and the ability to work in a fast-paced, agile environment.
- Excellent communication skills, with the ability to translate complex technical concepts for diverse stakeholders.