Machine Learning Engineer, LLM Training & Customization (Remote)
New Today
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)
- Location:
- Nottingham, England, United Kingdom
- Salary:
- £125,000 - £150,000
- Job Type:
- FullTime
- Category:
- Engineering