Job Description
Are you ready to architect the intelligence of tomorrow?
Nebula Innovations is seeking a visionary Senior AI/ML Engineer to lead our next-generation research division. We are building the software stack for 2026 and beyond, focusing on autonomous agents, generative AI, and quantum-ready neural networks. If you are passionate about pushing the boundaries of what is possible with artificial intelligence, we want to hear from you.
As a key member of our elite engineering team, you will be responsible for designing scalable AI architectures that power our global products. You will work directly with C-level executives and top-tier researchers to define the roadmap for our AI infrastructure.
Responsibilities
- Lead R&D: Spearhead the research and development of cutting-edge Large Language Models (LLMs) and generative AI frameworks tailored for enterprise scalability.
- Architecture Design: Design and implement robust, fault-tolerant MLOps pipelines and inference engines optimized for high-throughput environments.
- Model Optimization: Work closely with data scientists to fine-tune models, reducing latency and improving accuracy through advanced quantization and pruning techniques.
- Technical Leadership: Mentor junior engineers and data scientists, conducting code reviews, and establishing best practices for AI development within the organization.
- Collaboration: Partner with product management and engineering teams to translate complex technical requirements into feasible, high-impact solutions.
- Future-Proofing: Stay ahead of industry trends in AI, including reinforcement learning and neural architecture search, to integrate emerging technologies into our stack.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related field from a top-tier institution.
- Experience: Minimum of 5+ years of professional experience in building, deploying, and maintaining production-grade AI/ML systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of deep learning architectures (Transformers, CNNs, RNNs).
- MLOps: Strong experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration (Kubernetes).
- Programming: Solid fundamentals in software engineering principles, including data structures, algorithms, and system design.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.