Applied AI Engineer - LLM & NLP

At Toku, we create bespoke cloud communications and customer engagement solutions to reimagine customer experiences for enterprises. We provide an end-to-end approach to help businesses overcome the complexity of digital transformation and deliver mission-critical CX through cloud communication solutions. Toku combines local strategic consulting expertise, bespoke technology, regional in-country infrastructure, connectivity, and global reach to serve the diverse needs of enterprises operating dquartered in Singapore, Toku supports customers across APAC and beyond, with a growing footprint across global markets.

As an Applied AI Engineer at Toku, you will focus on building, improving, and deploying real-world AI capabilities across speech-to-text, chatbots, and large language model–driven features used in production. This role combines hands‑on model development with applied research, where you will evaluate existing approaches, explore new techniques, and translate research insights into practical improvements in live systems. You will work closely with engineering teams to integrate models into production services while maintaining a strong delivery mindset.

You will thrive in this role if you enjoy balancing deep technical execution with curiosity-driven, applied research that directly shapes product outcomes.

• Train, fine‑tune, evaluate, and improve NLP, speech‑to‑text, and LLM‑based models used in production environments

• Work hands‑on with chatbots, summarisation, and language understanding features, including retrieval‑augmented generation (RAG) and vector‑based retrieval systems

• Design and run model evaluations, benchmarking existing approaches and validating improvements before deployment

• Read, assess, and experiment with relevant AI/ML research and emerging techniques, translating promising ideas into practical, production‑ready solutions

• Contribute to prompt design, model optimisation, and iterative experimentation to improve accuracy, latency, and reliability of deployed models

• Integrate models into existing backend services using Python‑based APIs, collaborating closely with backend engineers

• Ensure models are production‑ready, maintainable, and resilient when deployed in live customer‑facing systems

• Support investigation and resolution of AI‑related production issues in collaboration with engineering and platform teams

• Work closely with engineering teams to align AI capabilities with product requirements and platform constraints

• Communicate progress, trade‑offs, and technical decisions clearly in planning and delivery discussions

• Strong hands‑on experience with LLMs, NLP, or speech technologies, including training, fine‑tuning, and evaluating models in real‑world or production contexts

• Practical experience with Python‑based AI development (e.g. PyTorch and related ecosystems)

• Hands‑on experience reading, evaluating, and applying AI/ML research (e.g. papers, benchmarks, emerging techniques) and translating those insights into production‑ready model improvements

• A strong foundation in AI/ML fundamentals (e.g. mathematics, machine learning concepts, model behaviour and evaluation), typically supported by an academic background in AI, machine learning, computer science, or a closely related field

• Experience deploying or supporting AI models in production systems, including exposure to monitoring, iteration, and real‑world failure modes

• Ability to integrate models into existing backend services via Python APIs and…