Job Description
Shape the Future of Intelligence.
Nebula AI Solutions is at the forefront of the Generative AI revolution. We are seeking a visionary Senior AI & Machine Learning Engineer to lead the development of next-generation neural architectures. If you are passionate about pushing the boundaries of what's possible in Large Language Models (LLMs) and Computer Vision, we want to hear from you.
Our Culture:
We prioritize innovation, autonomy, and impact. As a key member of our technical team, you will work in a hybrid environment that fosters creativity and rapid prototyping. We offer competitive equity packages, top-tier healthcare, and a commitment to work-life balance.
What You Will Do:
Architect scalable machine learning pipelines, optimize model performance for real-time inference, and mentor junior engineers. You will bridge the gap between theoretical research and production-grade deployment, ensuring our AI products are robust, fair, and efficient.
Responsibilities
- Design, train, and deploy state-of-the-art deep learning models (transformers, diffusion models).
- Optimize existing models for latency, throughput, and memory efficiency using techniques like quantization and pruning.
- Collaborate with product managers and data scientists to define technical requirements and roadmap.
- Implement MLOps best practices for CI/CD pipelines, model monitoring, and automated retraining.
- Conduct rigorous code reviews and technical mentoring for the engineering team.
- Research and integrate cutting-edge papers from top AI conferences (NeurIPS, ICML, etc.).
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field (or equivalent experience).
- 5+ years of professional experience in AI/ML engineering, with at least 2 years specifically in Generative AI or NLP.
- Strong proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of deploying models to production environments serving millions of users.
- Deep understanding of statistical modeling, optimization algorithms, and distributed systems.