Senior AI/ML Engineer - 2026 Vision

Shape the Future of Technology in 2026

We are looking for a visionary Senior AI/ML Engineer to join Nebula Innovations and lead our strategic initiatives for the 2026 roadmap. As we prepare for the next major leap in artificial intelligence, you will be at the forefront of designing scalable systems and deploying advanced neural architectures that redefine industry standards.

Why This Role?

At Nebula, we don't just follow trends; we define them. You will work in a high-performance environment, collaborating with top-tier researchers and engineers to build the intelligent infrastructure of tomorrow.

Key Responsibilities

You will be responsible for the full lifecycle of machine learning development, from theoretical research to production deployment:

• Architect 2026-Ready AI Systems: Design and implement robust machine learning pipelines that are scalable, efficient, and resilient.
• Model Optimization: Push the boundaries of deep learning by optimizing neural network architectures for real-time inference and edge computing.
• Research & Innovation: Conduct experimental research to integrate emerging technologies, including Generative AI and Predictive Analytics, into core products.
• Production Deployment: Deploy models to cloud infrastructure (AWS/Azure) using containerization technologies (Docker/Kubernetes).
• Team Leadership: Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
• Data Strategy: Collaborate with data engineering teams to ensure high-quality data ingestion and processing pipelines.

Qualifications

We are looking for candidates with a strong foundation in computer science and a passion for the future of AI:

• Education: Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Experience: 5+ years of professional experience building and deploying production-grade machine learning models.
• Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (MLflow, Kubeflow) is highly preferred.
• Domain Knowledge: Strong background in Natural Language Processing (NLP) or Computer Vision is a plus.
• Problem Solving: Ability to tackle complex, unstructured problems with creative algorithmic solutions.
• Communication: Excellent written and verbal communication skills to bridge the gap between technical and non-technical stakeholders.