Lucidworks-posted 4 months ago
$100,000 - $125,000/Yr
Full-time • Entry Level
101-250 employees

As an Associate Machine Learning Engineer at Lucidworks, you’ll have the opportunity to apply foundational AI concepts in a hands-on, production environment. In this role, you’ll work on projects that bring theory into practice, contributing to systems that impact real users while receiving feedback and mentorship to support your growth. You’ll gain experience with areas such as large language models (LLMs), search relevance, and natural language processing (NLP) challenges, while also exploring the applications of generative AI in search and information retrieval. Your work will include implementing algorithms from documentation and examples, modifying and extending existing code, writing tests, and interpreting results with guidance from senior engineers. This is a highly collaborative role, where you’ll engage with a diverse, distributed team across multiple time zones. You’ll be encouraged to ask questions, share ideas, and learn continuously as you develop your technical and professional skills.

  • Learn and assist in assessing models and understanding model selection for different use cases
  • Support experiments and evaluation for search-specific tasks
  • Contribute to integrating pre-trained language and embedding models into search, agentic, and recommendation pipelines
  • Support the development of automated model training, assessment, and deployment processes
  • Contribute to software and tooling that improves automation and service reliability
  • Stay current on AI best practices and share learnings with the team
  • Participate in design discussions and contribute fresh perspectives
  • Collaborate with software team members in a fast-paced Agile environment
  • Grow your skills while working effectively with distributed teams
  • All other duties as assigned
  • 0-2 years of professional experience OR relevant internship/project experience
  • Bachelor's degree in Computer Science, Data Science, Mathematics, or related field (or equivalent experience)
  • Strong programming fundamentals in Python
  • Familiarity with common data science libraries such as pandas, numpy, and transformers/sentence-transformers
  • Basic exposure to large language models through coursework, tutorials, or personal projects
  • Basic understanding of PyTorch
  • Basic understanding of microservices concepts and containerization (Docker knowledge preferred)
  • Eagerness to learn cloud technologies and production AI systems
  • Experience with version control (Git) is a plus
  • Exposure to LLM fine-tuning techniques (e.g., LoRA, QLoRA) is preferred
  • Familiarity with prompt engineering, context design, and LLM evaluation methods
  • Personal or academic projects demonstrating AI implementation or LLM usage or contributions to open-source AI projects are a plus
  • Acceptable background check
  • Experience with version control (Git)
  • Exposure to LLM fine-tuning techniques (e.g., LoRA, QLoRA)
  • Familiarity with prompt engineering, context design, and LLM evaluation methods
  • Personal or academic projects demonstrating AI implementation or LLM usage or contributions to open-source AI projects
  • Discretionary variable bonus
  • Top-notch medical, dental and vision coverage
  • Equity
  • A variety of voluntary benefits
  • Flexible time off
  • Various leave policies
  • Region-specific benefits
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