clients CloudDevs

Remote AI (LLM) Fullstack Engineer

Location

Worldwide

Job Type

Full-time

Experience

N/A

Salary

N/A

Skill Set

Role

Full Stack Programming

Job Details

Time zones: EST (UTC -5), CST (UTC -6), MST (UTC -7), PST (UTC -8), ART (UTC -3), UTC -4, UTC -4:30, UTC -3, UTC -2, SBT (UTC +11), GMT (UTC +0), CET (UTC +1), EET (UTC +2), MSK (UTC +3), AST (UTC -4), FKST (UTC -3), NST (UTC -3:30), CEST (UTC +2), BST (UTC +1), JST (UTC +9), CST (UTC +8), WIB (UTC +7), MMT (UTC +6:30), BST (UTC +6), NPT (UTC +5:45), IST (UTC +5:30), UZT (UTC +5), IRDT (UTC +4:30), GST (UTC +4), LINT (UTC +14), TOT (UTC +13), CHAST (UTC +12:45), LHST (UTC +10:30), AEST (UTC +10), ACST (UTC +9:30), ACWST (UTC +8:45), MART (UTC -9:30), NUT (UTC -11)


CloudDevs is helping world-class, venture-backed AI startups find talented AI full-stack developers. You will be employed by one of these startups and play an integral role in their early-stage growth.


Minimum qualifications:

  • Proven track record of shipping software and successfully released apps (please include names and links on your resume)
  • 5+ years of commercial experience using React or Vue or any JS framework on the front end and major frameworks like python/ go/Rails/elixir/java/flask/NodeJS on the backend.
  • Bachelor's degree in Computer Science or equivalent practical experience
  • 7+ years of work experience as a software engineer or relevant experience
  • Strong and confident communicator in English
  • Strong problem solver
  • Comfortable with collaboration and open communication across distributed teams


work:

  • Design, develop, and implement custom latest generative LLMs (e.g. models similar to GPT or ChatGPT or GPT4) and discriminative LLMs (e.g. models similar to BERT).
  • create wrapper apps based on ChatGTP and other LLMs
  • Design, develop, and implement systems for AI alignment, Reinforcement Learning with Human Feedback (RLHF) instruction models, and AI guardrails.
  • Conduct rigorous tests to evaluate LLMs across standardized performance benchmarks and custom evaluations.
  • Employ cutting-edge Natural Language Processing (NLP) and Machine Learning (ML) techniques to solve complex natural language problems.
  • Translate technical findings into clear, actionable insights for a non-technical audience.


Here’s what you need:

  • Experience with generative LLM fine-tuning and prompt engineering
  • Experience with deep learning frameworks
  • Experience with Hugging Face Transformers and other open-source NLP/NLG modules