This role is for one of the Weekdays clients
We are looking for an LLM Engineer to design finetune and deploy large language models that drive our cuttingedge AI solutions. You will collaborate with crossfunctional teams to build intelligent scalable systems enabling seamless interactions with our Universal AI Teammate. Your work will focus on delivering highperforming models that align with realworld applications.
Key Responsibilities
- Model Development: Finetune and optimize large language models (LLMs) for diverse applications and specific use cases.
- Pipeline Design: Build and maintain data pipelines to preprocess clean and manage datasets for both training and inference.
- Integration: Partner with backend engineers to integrate LLMs into product infrastructure ensuring reliability and scalability.
- Performance Optimization: Enhance model efficiency reduce response times and improve accuracy for production environments.
- Research & Innovation: Stay at the forefront of NLP and deep learning advancements applying cuttingedge techniques to elevate our AI platform.
- Evaluation & Testing: Develop metrics and benchmarks to assess model performance and ensure exceptional quality standards.
What We re Looking For
- Experience: 1 years of handson experience in NLP and working with largescale language models.
- Technical Skills:
- Proficiency in Python and frameworks like TensorFlow or PyTorch.
- Experience with transformerbased architectures (e.g. GPT BERT LLaMA).
- Familiarity with tools like Hugging Face LangChain or similar libraries.
- Understanding of MLOps for deploying and managing models in production environments.
- Data Expertise: Expertise in handling large datasets and implementing advanced preprocessing techniques.
- ProblemSolving: Proven ability to tackle complex technical challenges related to LLMs.
- Collaboration Skills: Strong communication skills and experience working with product managers backend engineers and designers.
- Research Mindset: A passion for staying current with the latest breakthroughs in AI and NLP.
problem-solving,hugging face transformers,numpy,distributed computing,natural language processing (nlp),attention mechanisms,pandas,cloud platforms (aws, azure, gcp),large language models (llms),python,training large-scale models using gpus/tpus,scikit-learn,tensorflow,machine learning frameworks,pytorch,learning,aws,machine learning,prompt engineering,models,nlp