About this role
Summary: Join Red Alpha Cybersecurity as an AI Engineer to build and deploy AI-powered MVPs, optimize models, and bridge technical research with business applications. This role involves applied AI engineering, prototyping, and strategic thinking within a fully sponsored training program.
Red Alpha Cybersecurity is hiring aspiring AI Engineers who want to work on real-world AI applications, from model design and optimization to rapid MVP development. You'll be part of a team building cutting-edge AI capabilities that power next-gen products across industries.
### What You’ll Be Doing
Applied AI Engineering & Prototyping
- Build and deploy AI-powered MVPs together with data science teams
- Design and optimise AI models for practical, high-impact use cases
- Apply advanced AI methods like meta-learning, prompt engineering, and in-context learning
- Leverage tools like VLLM, Nvidia Triton, and Nvidia NIMs to deliver scalable solutions
Model Training, Optimisation & Evaluation
- Train, fine-tune, and evaluate models using industry-standard frameworks
- Benchmark and monitor performance of deployed AI systems
- Optimise AI pipelines for efficiency, speed, and scalability in production environments
Research Translation & Strategic Thinking
- Bridge the gap between technical research and business applications
- Identify how emerging AI approaches can support new products and turnkey solutions
- Support end-to-end prototyping and deployment of POCs involving LLMs, computer vision, and graph-based AI
### What You Should Know or Be Eager to Learn
Preferred Technical Skills (not mandatory)
- Python programming and working with open-source libraries
- Deep learning tools: PyTorch, Hugging Face, PyTorch Geometric
- Model types: Transformers, LSTMs, RNNs, GNNs, Heterogeneous GNNs (HGNNs)
- Concepts: Graph theory, reinforcement learning, agentic AI, AI reasoning
- Infrastructure tools: Nvidia NIMs, Nvidia Triton, VLLM
Mindset We Look For
- Strong problem-solving and critical-thinking skills
- Intellectual curiosity and willingness to dive deep into technical challenges
- Ability to balance innovation with practical business needs
All selected candidates will undergo a 12-week, fully sponsored on-job-training with allowance, before being deployed full-time for 3 years.