AI Developer 2

Job highlights

• Full time. Disclaimer: This job posting has been aggregated from external source
• Experience with Hugging Face Transformers,LangChain,OpenAI APIs. Strong knowledge of machine learning libraries: scikit-learn,XGBoost,LightGBM.
• Experience with dimensionality reduction techniques for feature selection.

Job Summary

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today!

Key Responsibilities

• Develop and fine-tune LLMs (GPT, BERT, T5, LLaMA, Mistral) for text generation, summarization, translation, and question-answering tasks.
• Work with transformer-based architectures, understanding self-attention mechanisms, token embeddings, and model interpretability.
• Implement custom tokenization techniques, text embedding models (SentenceBERT, OpenAI Embeddings, Cohere, etc.), and efficient inference optimizations.
• Apply prompt engineering and prompt tuning techniques to optimize model responses.
• Work with LangChain and LLM orchestration frameworks to build AI-powered applications.
• Build Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, Weaviate, ChromaDB.
• Work with Hugging Face Transformers, spaCy, NLTK, and OpenAI APIs.

Technical Skills

• Proficiency in Python
• Experience with Hugging Face Transformers, LangChain, OpenAI APIs
• Strong knowledge of machine learning libraries: scikit-learn, XGBoost, LightGBM
• Experience with Retrieval-Augmented Generation (RAG): Faiss, Pinecone, Weaviate, ChromaDB
• Training, fine-tuning, and optimizing transformer models (BERT, GPT, T5, LLaMA)
• Deep understanding of self-attention, positional embeddings, sequence modeling
• Strong NLP expertise: Named Entity Recognition (NER), topic modeling, text embeddings
• Good grasp of linear algebra: vectors, matrices, eigenvalues, eigenvectors etc
• Expertise in gradient descent, backpropagation, activation functions, loss functions
• Experience with dimensionality reduction techniques for feature selection
• Knowledge of time-series forecasting, anomaly detection, and probabilistic modeling
• Understanding of model serving techniques, including REST APIs and real-time inference.

Qualifications

• Bachelors degree in computer science, software engineering, data science, information systems, machine learning, or a related field, or equivalent experience required.
• 2+ years of experience in MLOps engineering, machine learning engineering, platform engineering, DevOps engineering, software engineering, or a related technical field required.
• Certification in cloud platforms, DevOps, machine learning, automation, container orchestration, or platform engineering preferred.
• Certification in cloud engineering, infrastructure automation, machine learning operations, or software delivery practices preferred.

Full time

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.