Job Description
We are seeking a visionary Senior AI Engineer to lead our research initiatives and help define the technological landscape of 2026. If you are passionate about the future of Artificial Intelligence and want to build the neural networks of tomorrow, we want to hear from you.
Role Overview:
In this role, you will be at the forefront of innovation, working on large-scale machine learning systems that power our core products. You will bridge the gap between theoretical research and practical application, ensuring our AI solutions are scalable, robust, and efficient.
What You Will Do:
- Design and implement end-to-end deep learning pipelines for NLP and Computer Vision applications.
- Optimize model inference latency and reduce resource consumption for production environments.
- Collaborate with cross-functional teams to translate business requirements into technical AI solutions.
- Stay ahead of the curve by researching and integrating state-of-the-art algorithms and libraries.
- Mentor junior engineers and contribute to our open-source AI ecosystem.
Qualifications:
- Master’s or PhD degree in Computer Science, Mathematics, or a related technical field.
- Minimum of 5 years of professional experience in Machine Learning or Deep Learning.
- Strong proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Experience with MLOps tools such as Docker, Kubernetes, and MLflow.
- Proven track record of deploying high-impact AI models into production.
Responsibilities
- Model Architecture: Design novel neural architectures to improve accuracy and efficiency of our models.
- Production Deployment: Oversee the MLOps lifecycle, ensuring models are deployed, monitored, and updated continuously.
- Performance Tuning: Conduct rigorous testing to optimize model performance on edge devices and cloud infrastructure.
- Research & Innovation: Publish papers and present findings at top-tier AI conferences.
- Code Quality: Write clean, maintainable, and well-documented code that adheres to industry best practices.
Qualifications
- Education: MS or PhD in Computer Science, AI, or a related quantitative discipline.
- Technical Skills: Expert knowledge of NLP, Transformers, or Generative AI models.
- Programming: Deep understanding of C++ and Python for high-performance computing.
- Communication: Ability to articulate complex technical concepts to non-technical stakeholders.
- Problem Solving: Strong analytical skills with a focus on algorithmic optimization.