Job Description
Are you ready to define the technology landscape of 2026? Apex Future Tech is seeking a visionary Senior Generative AI Engineer to lead our next-generation language model initiatives. We are building the intelligence layer for the future, and we need someone with deep expertise in Large Language Models (LLMs), Transformer architectures, and ethical AI deployment.
In this role, you won't just be maintaining legacy systems; you will architect the future of human-computer interaction. You will work at the intersection of research and production, pushing the boundaries of what is possible with AI today to solve tomorrow's problems.
Why Join Us?
- Work with state-of-the-art models (GPT-4, Llama 3, Claude).
- Competitive equity package for long-term impact.
- Flexible remote-first culture with a premium office in SF.
Join a team of world-class researchers and engineers dedicated to creating AI that is not only powerful but safe, scalable, and beneficial for humanity.
Responsibilities
- Design and implement scalable inference pipelines for Large Language Models, optimizing for latency and throughput.
- Conduct cutting-edge research on fine-tuning techniques (LoRA, P-Tuning) and Reinforcement Learning from Human Feedback (RLHF).
- Collaborate with cross-functional teams to integrate AI agents into complex software ecosystems.
- Ensure model robustness, fairness, and safety through rigorous testing and bias mitigation strategies.
- Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning.
- Stay ahead of the curve by monitoring emerging AI trends and evaluating new model architectures.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in Machine Learning, NLP, or Deep Learning.
- Strong proficiency in Python, PyTorch, and TensorFlow.
- Extensive experience with Hugging Face Transformers, LangChain, or similar frameworks.
- Proven track record of deploying models to production environments (AWS, GCP, or Azure).
- Demonstrated ability to think critically about AI ethics, alignment, and safety.