Principal Large Language Model Engineer

SmartAsset-posted 2 months ago
$190,000 - $236,000/Yr
Full-time • Mid Level
251-500 employees
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At SmartAsset, you will join a team of data scientists, analysts, and ML engineers that are at the forefront of AI/ML application for the company. You will have the opportunity to work cross-functionally with leaders from different teams (Marketing, Product, Sales, and Technology), and with our growing Data team. The role involves designing and implementing a high-performance, scalable, and reliable LLM service using Python and various LLM services to power applications and business needs. You will also be responsible for building search engines and recommendation engines, collaborating with business leaders to identify LLM use cases, and mentoring junior developers.

  • Design and implement a high-performance, scalable and reliable LLM service using Python and Cloud technologies.
  • Design and develop RAG pipelines and build search engines and recommendation engines on domain-specific corpus.
  • Collaborate with business leaders to understand their needs and challenges, and identify potential LLM use cases.
  • Monitor LLM performance and make improvements to ensure acceptable response times based on use cases.
  • Participate in code reviews and provide guidance to junior developers.
  • Mentor LLM and AI Engineers to help deliver the AI use cases across the company.
  • Perform LLM modeling, fine-tuning, and deployment of advanced AI technology solutions.
  • Utilize strong communication skills to convey technical concepts and collaborate with cross-functional teams.
  • Develop and maintain comprehensive documentation, including technical specifications and user guides.
  • Ensure data privacy and security compliance while working with LLMs.
  • Provide support and training to internal teams as needed.
  • Bachelor’s degree or U.S. equivalent in Computer Engineering, Computer Science, Data Science, or related field, plus 5 years of professional experience as a Software Developer or Software Engineer involving developing LLM applications.
  • In lieu of a Bachelor's degree, a Master's degree or U.S. equivalent in a related field plus 3 years of professional experience is acceptable.
  • 3 years of professional experience utilizing Python programming, building ETL pipelines, and working with Transformer architecture models.
  • 3 years of professional experience working with Cloud Platforms (including AWS, GCP, and Azure) and Vector databases (including MongoDB).
  • 3 years of professional experience utilizing LLM concepts including model fine-tuning and transfer learning.
  • 3 years of professional experience utilizing LLM frameworks (including Hugging Face Transformers) and integrating with Python.
  • 3 years of professional experience automating and scaling web frameworks (including FastAPI and Django) for building production-ready applications.
  • 3 years of professional experience building conversational chatbots using LLMs.
  • 3 years of professional experience presenting complex concepts to both technical and non-technical audiences.
  • 3 years of professional experience working in a cross-functional team and collaborating with stakeholders.
  • 3 years of professional experience with DevOps toolsets and working with RDBMS databases including MySQL, SQL Server, and PostgreSQL.
  • 3 years of professional experience utilizing Docker, Kubernetes, and CI/CD tools.
  • Experience building machine learning models including Random Forest, Logistic Regression, Linear Regression, Support Vector Machines (SVM), XGBoost, and LightGBM.
  • Experience working with clustering models, including K-Means, DBSCAN, Gaussian Mixture Models, and Agglomerative Clustering.
  • Telecommuting from anywhere in the U.S.
  • Medical, Dental, Vision - multiple packages available based on your individualized needs.
  • Life/AD&D Insurance - basic coverage at 100% company paid, additional supplemental available.
  • Supplemental Short-term and Long-term Disability.
  • FSA: Medical and Dependant Care.
  • 401K.
  • Equity packages for each role.
  • Time Off: Vacation, Sick and Parental Leave.
  • EAP (Employee Assistance Program).
  • Pet Insurance.
  • Home Office Stipend.
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