AI/ML Developer

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.
• Good 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

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