AI Fullstack Engineer
- Latin America
- Full-Time
- 4 applicants
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 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+ yrs of commercial experience using React or Vue or any JS framework on the front-end and major frameworks like Rails /python/ go/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
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