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Machine Learning Engineer, LLM Training & Customization (Remote)
Posted 9 hours 13 minutes ago by NLP PEOPLE
Permanent
Full Time
Training Jobs
Nottinghamshire, Nottingham, United Kingdom, NG1 1
Job Description
What You'll Do 
- Train and fine-tune Large Language Models (LLMs) based on client domains and industry-specific data.
- Design, develop, and optimize custom AI workflows that integrate LLMs into production environments.
- Utilize LangChain, CrewAI, and LangFlow to orchestrate complex LLM-based applications.
- Implement and optimize retrieval-augmented generation (RAG) techniques for better contextual responses.
- Work on data preparation pipelines, including tokenization, augmentation, and embedding optimizations.
- Develop scalable and efficient inference pipelines for deploying LLMs in production.
- Collaborate with software engineers to integrate AI models into real-world applications.
- Optimize model performance, latency, and cost to ensure smooth deployment at scale.
- Research and experiment with cutting-edge AI advancements in LLM fine-tuning and prompt engineering.
- 3+ years of experience in Machine Learning & NLP, with a focus on LLM training and deployment.
- Experience with LLM fine-tuning techniques such as LoRA, PEFT, and instruction tuning.
- Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- Hands-on experience with LangChain, CrewAI, and LangFlow (bonus points for deep expertise).
- Strong understanding of vector databases (Pinecone, Weaviate, FAISS) and embedding models.
- Experience building production-ready AI products, ensuring scalability and reliability.
- Deep knowledge of prompt engineering, tokenization strategies, and data augmentation for LLMs.
- Familiarity with ML-Ops best practices, cloud-based AI deployments, and GPU optimizations.
- A passion for AI-driven automation, custom model development, and pushing the boundaries of LLM capabilities.
- Experience deploying LLMs in low-latency, real-time environments.
- Strong background in serverless AI architectures and containerized deployments.
- Hands-on experience with Kubernetes, Docker, and cloud-based ML workflows (AWS/GCP/Azure).
- Knowledge of speech-to-text (STT), text-to-speech (TTS), or conversational AI.
InspHire
QualificationsSenior (5+ years of experience)
Language requirementsN/A
Specific requirementsN/A
Educational levelN/A
Level of experience (years)Senior (5+ years of experience)
NLP PEOPLE
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