Applied AI Engineer – LLM, NLP
Toku
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇮🇳 India
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSDockerEC2PythonPyTorch
About the role
- 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
- 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
- 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
Requirements
- Strong hands-on experience with LLMs, NLP, or speech technologies
- Practical experience with Python-based AI development (e.g. PyTorch and related ecosystems)
- Hands-on experience reading, evaluating, and applying AI/ML research
- A strong foundation in AI/ML fundamentals
- Experience deploying or supporting AI models in production systems
- Ability to integrate models into existing backend services via Python APIs
- 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)
- A proactive, problem-solving mindset with the ability to identify opportunities for improvement
- Strong collaboration and communication skills when working with engineers across different disciplines
Benefits
- Training and Development
- Discretionary Yearly Bonus & Salary Review
- Healthcare Coverage based on location
- 20 days Paid Annual Leave (excluding Bank holidays)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
NLPspeech-to-textLLMmodel evaluationmodel optimisationPythonAI/ML fundamentalsretrieval-augmented generationembeddingsvector-based retrieval
Soft skills
problem-solvingcollaborationcommunication