Job Description
We are at the forefront of the 2026 technological revolution, building the AI systems that will define the next decade. Apex Horizon Labs is seeking a visionary Senior AI Research Engineer to join our elite R&D division. You will be responsible for architecting the next generation of generative models and autonomous agents that power our enterprise solutions.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and production-grade software engineering. If you are passionate about pushing the boundaries of AI, optimizing large-scale neural networks, and shaping the future of 2026 technology, we want to hear from you.
Why Join Us?
- Work on cutting-edge 2026-ready AI architectures.
- Competitive compensation package with equity options.
- Flexible remote-first policy with a hub in San Francisco.
- Access to the latest hardware for high-performance computing.
Responsibilities
- Design and implement novel deep learning architectures for 2026 strategic goals, focusing on efficiency and scalability.
- Lead the training and fine-tuning of Large Language Models (LLMs) and multimodal systems.
- Optimize model inference speeds and reduce computational costs through quantization and pruning.
- Collaborate with cross-functional teams to integrate AI models into production environments.
- Conduct rigorous testing and validation to ensure model robustness and safety.
- Write and publish technical whitepapers to contribute to the global AI community.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related technical field.
- 5+ years of professional experience in machine learning research or software engineering.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of Natural Language Processing (NLP) and Transformer architectures.
- Experience with distributed training systems and cloud platforms (AWS, GCP, or Azure).
- Excellent problem-solving skills and ability to thrive in a fast-paced, innovative environment.