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Machine learning engineer, llm training & customization (remote)

Nottingham (Nottinghamshire)
NLP PEOPLE
Machine learning engineer
Posted: 9 September
Offer 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.


What You’ll Bring

* 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.


Bonus Points

* 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.


Company

InspHire


Qualifications

Senior (5+ years of experience)


Language requirements

N/A


Specific requirements

N/A


Educational level

N/A


Level of experience (years)

Senior (5+ years of experience)

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