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Machine Learning Engineer, LLM Training & Customization (Remote)

NLP PEOPLE
Nottingham
4 days ago
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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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