[TEST] Forward Deployed Engineer

Red Alpha; Singapore; On-site; SGD 90,000 - 130,000; Full time

Benefits offered by this job

12-week sponsorship training

Job summary

Red Alpha Cybersecurity is seeking aspiring AI Engineers to build real-world AI applications, from model design to rapid MVP development and deployment.

You will collaborate with data science teams to train, benchmark, and deploy AI systems using PyTorch, Transformers, and graph-based methods, including LLMs, with a 12-week on-job training.

Join a fast-paced environment across industries, with hands-on prototyping and deployment lasting 3 years after training.

Qualifications

• Python programming and open-source libraries experience.
• Deep learning tools and frameworks experience.
• Familiarity with Transformers and graph neural networks.

Responsibilities

• Build and deploy AI-powered MVPs with data science teams.
• Design and optimise AI models for practical use cases.
• Bridge technical research and business applications in AI projects.
• Prototype and deploy POCs involving LLMs and graph-based AI.

Skills

Python programming

Deep learning

Research & prototyping

Tools

PyTorch

Transformers

PyTorch Geometric

Hugging Face

VLLM

Nvidia Triton

Nvidia NIMs

GNNs

HGNNs

Job description

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.