Job Description
Architect the Next Generation of Intelligence
Join OmniFuture Systems as a Senior Generative AI Engineer and lead the charge in redefining human-machine interaction. We are not just building models; we are crafting the cognitive architecture of tomorrow. In this pivotal role, you will harness the power of Large Language Models (LLMs) and diffusion techniques to solve complex, real-world problems with unprecedented creativity and efficiency.
At OmniFuture, we value audacity, technical excellence, and a relentless pursuit of innovation. If you are ready to move beyond the hype and build scalable, ethical, and transformative AI systems, we want to meet you.
Why Join Us?
- Equity-First Culture: Own a piece of the future as we scale to redefine the tech landscape.
- Top-Tier Talent: Collaborate with Ph.D.-level researchers and industry veterans.
- Cutting-Edge Stack: Work with the latest in PyTorch, TensorFlow, and proprietary cloud infrastructure.
- Impactful Work: Your models will directly influence millions of users worldwide.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale generative models to achieve state-of-the-art performance in NLP and multimodal tasks.
- Infrastructure Optimization: Engineer efficient pipelines for data preprocessing, training, and inference using distributed computing frameworks (e.g., Ray, Kubernetes).
- RAG Implementation: Develop robust Retrieval-Augmented Generation systems to ensure model accuracy and reduce hallucinations.
- Research & Experimentation: Stay at the forefront of AI research, implementing novel architectures and algorithms to maintain our competitive edge.
- Code Review & Mentorship: Lead technical reviews, mentor junior engineers, and foster a culture of continuous learning and technical excellence.
- Ethical AI: Advocate for responsible AI practices, ensuring fairness, transparency, and robust safety guardrails in all deployed models.
Qualifications
- Experience: 5+ years of professional experience in software engineering or machine learning, with at least 2 years specifically focused on generative AI or deep learning.
- Technical Skills: Strong proficiency in Python, PyTorch, or TensorFlow. Deep understanding of transformer architectures, attention mechanisms, and diffusion models.
- Tooling: Experience with MLOps tools (MLflow, DVC, Weights & Biases) and cloud platforms (AWS, GCP, or Azure).
- Education: BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver scalable solutions under tight deadlines.
- Communication: Excellent written and verbal communication skills; ability to translate complex technical concepts for diverse stakeholders.