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.

.

Bachelor's 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.

What Cencora offers

​Benefit offerings outside the US may vary by country and will be aligned to local market practice. The eligibility and effective date may differ for some benefits and for team members covered under collective bargaining agreements.

Full time

Affiliated Companies

Affiliated Companies: CENCORA BUSINESS SERVICES INDIA PRIVATE LIMITED

Equal Employment Opportunity

Cencora is committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status or membership in any other class protected by federal, state or local law.

The company’s continued success depends on the full and effective utilization of qualified individuals. Therefore, harassment is prohibited and all matters related to recruiting, training, compensation, benefits, promotions and transfers comply with equal opportunity principles and are non-discriminatory.

Cencora is committed to providing reasonable accommodations to individuals with disabilities during the employment process which are consistent with legal requirements. If you wish to request an accommodation while seeking employment, please call 888.692.2272 or email [email protected]. We will make accommodation determinations on a request-by-request basis. Messages and emails regarding anything other than accommodations requests will not be returned