Job Description
Are you ready to architect the technological landscape of 2026? Apex Future Technologies is seeking a visionary Lead Generative AI Engineer to spearhead our next-generation AI initiatives. We are building the foundational models that will power the enterprise of tomorrow. If you are passionate about the future of Artificial Intelligence and want to solve the hardest problems in LLM scalability and ethics, this is your opportunity to lead.
Why Join Us?
At Apex Future Technologies, we don't just predict the future; we build it. We offer a competitive salary, equity packages, and a culture that prioritizes innovation over convention. You will work directly with C-level executives and world-class researchers to define the roadmap for 2026 and beyond.
Responsibilities
- Model Architecture: Design and implement cutting-edge Generative AI models, including Large Language Models (LLMs) and multimodal systems, optimized for 2026-scale deployment.
- Research & Innovation: Push the boundaries of current state-of-the-art (SOTA) techniques in transformer architecture, reinforcement learning, and prompt engineering.
- Team Leadership: Mentor a team of junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Production Deployment: Oversee the end-to-end ML lifecycle, ensuring models are scalable, secure, and deployed via robust MLOps pipelines.
- Ethical AI: Establish frameworks for AI safety, bias mitigation, and transparency to ensure responsible AI development.
- Strategic Roadmap: Collaborate with product leadership to define technical requirements and strategic milestones for future products.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related technical field with a focus on Machine Learning or Deep Learning.
- Experience: 5+ years of experience in software engineering and at least 3 years specifically in Generative AI or Natural Language Processing (NLP).
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Deep understanding of Transformer models (BERT, GPT, T5) and fine-tuning methodologies.
- Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and deliver innovative solutions in high-pressure environments.
- Communication: Exceptional verbal and written communication skills, with the ability to translate complex technical concepts for non-technical stakeholders.