AI-ML Engineer

3 months ago


Doha, Qatar Braintrust Full time

We are seeking an experienced AI-ML Engineer to join our fast-paced and dynamic team. This role is for individuals who are natural leaders, critical thinkers, extremely passionate about their work and can work well in small teams with minimum guidance. You will likely be the only AI-ML Engineer on our team for at least 6 months, and will be critical to developing the LLM infrastructure that we use to power our platform.

Qualifications

  • Minimum 3 years of full-time, professional engineering experience
  • Minimum of 1 year experience working on production-grade, LLM systems
  • Eager to take initiative and work independently for extended periods (e.g., expect to be the only AI-ML engineer on staff for at least 6 months)
  • Strong collaboration skills for working in a remote, cross-cultural team (e.g., you are proactive about finding solutions before escalating issues)

Technical Skills

  • Expertise in designing and implementing production-grade LLM systems (with an interest in designing novel agentic AI applications)
  • Strong background in LLM evaluation methodologies (e.g., DeepEval, HELM, LangChain Evaluators)
  • Proficiency in LLM techniques, including:
    • Prompt engineering
    • Few-shot learning
    • Parameter-efficient fine-tuning (e.g., LoRA, P-tuning)
  • Deep understanding of Retrieval Augmented Generation (RAG) techniques and architectures (e.g., document chunking, questions decomposition, subquery optimization)
  • Experience utilizing modular LLM development frameworks like DSPy
  • Advanced conversational AI features:
    • Context-aware response generation
    • Active learning for continuous model improvement
  • Vector databases and similarity search algorithms
  • Proficiency with the other following tools, frameworks and platforms:
    • LangChain
    • LlamaIndex
    • Vector DBs
    • Similarity search
    • AWS Sagemaker
  • Familiarity with ethical AI principles and techniques for mitigating bias in LLM-based systems
  • Experience with multi-modal models integrating text, vision, and potentially audio

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