Job Description
We are Apex Future Systems, a pioneering force in autonomous AI agents. We are looking for a visionary Senior Generative AI Engineer to lead the development of next-generation Large Language Models (LLMs) and multi-modal agents designed for the year 2026 and beyond.
In this role, you will bridge the gap between theoretical research and scalable production engineering. You will architect systems that are not only intelligent but also ethical, efficient, and adaptable to the rapidly evolving landscape of artificial general intelligence.
Join a team where your work will define the standard for human-AI interaction and shape the future of enterprise automation.
Responsibilities
- Model Architecture: Design and implement proprietary foundation models and fine-tuning pipelines for specific enterprise verticals.
- Optimization: Apply advanced quantization, pruning, and distillation techniques to reduce latency and cost without sacrificing accuracy.
- Research & Development: Stay at the forefront of the AI landscape, experimenting with novel architectures like MoE (Mixture of Experts) and state-space models.
- Deployment: Lead the MLOps strategy to ensure seamless, high-availability deployment of models in cloud and edge environments.
- Evaluation: Establish rigorous evaluation frameworks to measure model performance, safety, and alignment with human values.
- Cross-Functional Leadership: Collaborate with product managers, security teams, and legal experts to ensure responsible AI deployment.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Deep Learning or Natural Language Processing.
- Experience: 5+ years of professional experience in AI/ML engineering, specifically with LLMs (e.g., GPT, Llama, Mistral).
- Programming: Proficiency in Python, PyTorch, and TensorFlow. Experience with C++ for high-performance inference is a major plus.
- Tools: Strong understanding of Hugging Face, LangChain, and modern vector database architectures (e.g., Pinecone, Milvus).
- Problem Solving: Demonstrated ability to tackle complex mathematical and engineering challenges in model training and optimization.
- Communication: Excellent written and verbal communication skills for translating technical concepts to non-technical stakeholders.