Applied AI Engineer – LLM, NLP

Job not on LinkedIn

🕒 December 29, 2025

🌐 India, Netherlands, +2 more countries – Remote

🇮🇳 India – Remote 🇳🇱 Netherlands – Remote 🇸🇬 Singapore – Remote 🇭🇰 Hong Kong – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🗣️ LLM Engineer

👻 Ghost score 45%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Toku

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

✈️ Travel

💰 $5M Series A on 2022-10

Consulting • Logistics • Travel

Toku is a company that specializes in AI-powered communication solutions, focusing particularly on customer engagement and business telephony. They offer a wide range of products, including conversational AI platforms, AI voice agents, and business telephony solutions for platforms like Microsoft Teams and Zoom Phone. Their services also include customer engagement tools such as contact centers, campaign managers, and feedback management systems. Toku is particularly focused on enhancing customer experience (CX) in the APAC region with solutions tailored to address unique language and communication challenges in the area. Additionally, Toku provides embedded communication solutions like programmable voice and messaging, user verification, and number masking to enhance security and efficiency in client communications. They cater to various industries including government, fintech, insurance, and travel, aiming to provide omnichannel and seamless digital experiences.

📋 Description

• 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

🎯 Requirements

• 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 • 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 work effectively within a microservices-based environment • Familiarity with retrieval-augmented generation (RAG), embeddings, and vector-based retrieval systems • Working knowledge of AWS-based environments and AI tooling (e.g. EC2, SageMaker, MLflow, Docker)

🏖️ Benefits

• Discretionary Yearly Bonus & Salary Review • Healthcare Coverage based on location • 20 days Paid Annual Leave (15 days for Malaysia based roles), plus other leave allowances