Responsibilities
- Research, design, develop, fine-tune, and evaluate LLMs, intelligent agents, and deep learning models for AI security and system optimisation.
- Create advanced tools for automated red-teaming, vulnerability detection, adversarial attack simulation, and intelligent defences.
- Implement and deploy AI/LLM-powered features as robust, scalable, and secure components within the client's security platforms.
- Optimise AI/LLM models for inference speed, cost-efficiency, and resource utilisation in production.
- Develop and maintain pipelines for end-to-end AI/LLM workflows covering data preprocessing, training, fine-tuning, validation, deployment, and monitoring.
- Proactively monitor model performance and behaviour in production, addressing safety, alignment, and security vulnerabilities.
- Apply software engineering best practices to AI/LLM workflows for secure and seamless deployments.
- Partner with cross-functional teams, including researchers and engineers, to productionise cutting-edge AI/LLM techniques and integrate them into the client's products.
- Translate technical advancements into practical solutions aligned with customer needs and business objectives.
- Communicate findings and solutions through documentation and presentations for data-driven decision-making.
- Develop tools and strategies to detect and mitigate vulnerabilities such as prompt injection and data poisoning threats.
- Investigate and utilise advancements in Reinforcement Learning from Human Feedback (RLHF) to improve AI model reliability and alignment.
- Continuously stay updated on industry trends and research to integrate state-of-the-art AI/LLM advancements into the platform.
Basic qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 3-5 years of professional experience, including hands-on experience developing, training, and deploying AI/LLM models.
- Familiarity with AI/LLM libraries and tools such as PyTorch, TensorFlow, Hugging Face Transformers, or similar frameworks.
- Understanding of LLM security vulnerabilities and implementing mitigation solutions.
- Proven expertise in deploying AI/ML models in production environments, with emphasis on secure deployments.
- Strong analytical and problem-solving skills applied to complex AI challenges.
- Experience fine-tuning and deploying large-scale language models, including using frameworks like vLLM or TGI.
- Familiarity with Reinforcement Learning from Human Feedback (RLHF) for improving LLM alignment and performance.
- Knowledge of vector databases (e.g., Pinecone, Weaviate) and their applications in AI workflows.
- Expertise with cloud platforms and distributed computing for large-scale AI operations.
- Hands-on experience optimising models for cost, speed, and resource efficiency in production workflows.
- Demonstrating leadership in delivering robust, scalable, and secure AI/LLM-powered solutions.
- Collaborating effectively with cross-functional teams to align technical solutions with business needs and customer priorities.
- Developing innovative tools and methods to identify and mitigate security vulnerabilities within AI systems.
- Consistently applying advanced analytical techniques and operationalising data-driven insights to enhance platform efficiency and reliability.
Benefits
- Comprehensive Private Medical Coverage
- Support for Mental Health Expenses
- Life Insurance Options
- Attractive Compensation Package
About the company
C-Serv is a global IT consulting and workforce solutions firm operating across 50+ countries. We build high-performing teams for technology-led organisations, specialising in cybersecurity, cloud, AI, networking, and software engineering. We're 100% woman-owned, and our values — Empathy, Integrity, Collaboration, and Growth — govern how we hire, work, and treat every person we engage with.
Diversity & Inclusion
We champion diversity in every hire and are committed to equal opportunity regardless of race, religion, colour, national origin, sex, sexual orientation, gender identity, age, disability, marital status, or veteran status.
Tags & focus areas
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