Requirements

- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.

- Strong understanding of Python programming and common data structures.

- Basic knowledge of machine learning concepts, including supervised learning, unsupervised learning, model evaluation, overfitting, and feature engineering.

- Familiarity with Natural Language Processing concepts such as: Text preprocessing and normalization
- Tokenization, stemming, and lemmatization
- Text classification
- Named Entity Recognition
- Sentiment analysis
- Information extraction
- Semantic similarity and text embeddings.

- Experience with machine learning and NLP libraries such as: Scikit-learn

- Pandas and NumPy
- NLTK or spaCy
- Hugging Face Transformers
- PyTorch or TensorFlow.

- Basic understanding of transformer-based models, including BERT, T5, GPT-style models, or similar architectures.

- Familiarity with prompt engineering, large language models, and generative AI applications.

- Ability to clean, preprocess, label, and analyze text datasets.

- Understanding of common NLP evaluation metrics, including precision, recall, F1-score, accuracy, BLEU, ROUGE, and perplexity.

- Basic knowledge of REST APIs and experience integrating machine learning models into applications.

- Familiarity with Git and collaborative software development workflows.

- Strong analytical and problem-solving skills.

- Ability to read technical documentation and research papers.

- Valuable written and verbal communication skills.

- Willingness to learn new tools, models, and AI development practices.

Preferred Qualifications

- Academic, internship, or personal project experience in NLP or generative AI.

- Experience fine-tuning pretrained transformer models.





- Familiarity with vector databases and semantic search tools such as FAISS, Chroma, Pinecone, Weaviate, or similar platforms.

- Basic understanding of Retrieval-Augmented Generation systems.

- Exposure to LLM frameworks such as LangChain, LlamaIndex, or similar tools.

- Familiarity with data annotation, dataset quality validation, and model error analysis.

- Basic understanding of SQL, databases, Linux, Docker, and cloud platforms.

- Experience deploying models using FastAPI, Flask, or similar frameworks.

- Familiarity with experiment tracking and model versioning tools.

- Knowledge of responsible AI principles, including bias, privacy, security, and model hallucination management.

Responsibilities

- Assist in developing and improving NLP and machine learning solutions.

- Prepare, clean, label, and validate text datasets.

- Train, evaluate, and fine-tune machine learning and transformer-based models.

- Build prototypes for text classification, information extraction, chatbots, semantic search, summarization, and other NLP applications.

- Support the development of LLM and Retrieval-Augmented Generation pipelines.

- Perform model testing, error analysis, and performance optimization.

- Integrate AI models with internal products and APIs.

- Document experiments, model configurations, datasets, and technical findings.

- Collaborate with senior developers, data scientists, and product teams.

- Stay updated with developments in NLP, large language models, and generative AI.

Work Experience

1-3 years

Job Type

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.

📌 AI/ML Developer (Ahmedabad)
🏢 Infomize Technologies
📍 Ahmedabad