Job Description
Join the Pioneers of the AI Revolution
We are looking for a visionary Senior AI Research Engineer to lead our cutting-edge Generative AI initiatives. As we define the roadmap for 2026, our mission is to build the next generation of Large Language Models and multimodal AI systems that redefine human-computer interaction.
In this role, you won't just write code; you will architect the future of intelligence. You will work in a high-performance environment, collaborating with world-class researchers and product engineers to deploy scalable AI solutions that impact millions of users worldwide.
Why Join Us?
- Future-Ready Tech Stack: Work with the latest in PyTorch, TensorFlow, and distributed computing.
- Impactful Work: Directly contribute to models that solve complex, real-world problems.
- Competitive Compensation: A top-tier salary package plus performance bonuses.
- Flexible Culture: Remote-first hybrid model with a focus on autonomy and innovation.
Responsibilities
- Model Architecture & Training: Design, train, and fine-tune state-of-the-art generative models (LLMs, Diffusion Models) using large-scale datasets.
- Performance Optimization: Optimize inference pipelines for speed and cost-efficiency, reducing latency for real-time applications.
- R&D Leadership: Conduct advanced research to explore new architectures and methodologies, publishing findings where applicable.
- Collaboration: Partner with product managers and engineers to translate research breakthroughs into production-ready features.
- Code Review & Mentorship: Lead code reviews and mentor junior engineers, fostering a culture of technical excellence.
- Data Strategy: Assist in the development of data pipelines and quality assurance processes to ensure high-fidelity model outputs.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related quantitative field.
- Technical Expertise: Deep experience in Python, PyTorch, or TensorFlow with a strong understanding of Deep Learning frameworks.
- Experience: 5+ years of experience in research or engineering roles within AI/ML.
- Model Knowledge: Proven track record working with NLP, Transformers, or Generative Adversarial Networks (GANs).
- Problem Solving: Exceptional ability to debug complex issues and improve model accuracy and robustness.
- Communication: Excellent written and verbal communication skills for technical documentation and presentations.
- Tools: Proficiency in Git, Linux environments, and cloud platforms (AWS, GCP, or Azure).