Job Description
We are seeking a visionary Senior AI & Machine Learning Engineer to join Nebula Nexus and help define the technological landscape of 2026. As a pioneer in next-generation generative intelligence, we are building the infrastructure for the future of human-computer interaction. You will be at the forefront of developing Large Language Models (LLMs) and autonomous agent systems that will revolutionize industries.
In this role, you will not just maintain existing systems; you will architect the core of our AI ecosystem, working with a team of world-class researchers and engineers to solve complex, unsolved problems in artificial general intelligence.
Why Join Us?
- Future-Ready Role: This is a strategic position focused on the technologies that will define the 2026 tech landscape.
- Impact: Your work will directly influence millions of users globally.
- Equity Package: Competitive equity package reflecting our growth trajectory.
Responsibilities
- Architect & Build: Design, train, and deploy state-of-the-art deep learning models and LLMs at scale.
- R&D Leadership: Lead research initiatives into multimodal AI, reinforcement learning, and predictive analytics.
- System Optimization: Improve model inference speed and reduce latency in high-traffic environments.
- MLOps Implementation: Establish robust CI/CD pipelines for machine learning models, ensuring reproducibility and automated retraining.
- Technical Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Strategic Planning: Collaborate with product leaders to translate technical capabilities into tangible business solutions.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in building production-level machine learning systems.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and SQL.
- Modeling: Deep understanding of neural network architectures, transformers, and NLP techniques.
- Problem Solving: Proven track record of solving complex engineering challenges with data-driven solutions.
- Communication: Excellent verbal and written communication skills for technical and non-technical audiences.