Job Description
About Us: Apex Future Systems is pioneering the next generation of intelligent automation. As we accelerate toward the 2026 technology horizon, we are seeking a visionary Senior AI Research Engineer to lead our core development initiatives in Silicon Valley.
The Role: You will be at the forefront of Generative AI and Large Language Model (LLM) research. You will not just implement existing models; you will architect novel architectures that push the boundaries of what is possible in 2026 and beyond.
Why Join Us? Work with the best minds in the industry, competitive equity packages, and the chance to define the future of human-machine interaction.
Responsibilities
- Research & Development: Spearhead the design and implementation of proprietary AI models, focusing on scalability and efficiency for the 2026 landscape.
- Model Optimization: Optimize existing LLMs for reduced latency and enhanced reasoning capabilities in production environments.
- Prototype Creation: Build rapid prototypes and Minimum Viable Products (MVPs) to validate novel research concepts.
- Technical Leadership: Mentor junior researchers and engineers, fostering a culture of innovation and continuous learning.
- Collaboration: Partner with product managers and data scientists to translate complex research into actionable business solutions.
- Performance Evaluation: Establish rigorous testing protocols and metrics to ensure model accuracy and fairness.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of professional experience in AI research, machine learning engineering, or a related technical role.
- Programming: Expert proficiency in Python, PyTorch, and/or TensorFlow.
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Deep Learning, and Transformer architectures.
- Problem Solving: Demonstrated ability to tackle complex, ambiguous problems with innovative solutions.
- Communication: Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.