ML Engineer (Onsite, Lahore, Remittance Salary)

Requirements:

• Bachelors degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field.
• 1–2 years of hands-on experience in machine learning or AI development.
• Experience working on at least 1–2 end-to-end machine learning projects in academic or professional environments.
• Exposure to NLP, computer vision, or LLM-based applications is preferred.
• Proficiency in Python.
• Familiarity with machine learning libraries and frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Basic understanding of machine learning, neural networks, deep learning, NLP fundamentals, and transformer-based models.
  Basic understanding of REST APIs and backend integration.
• Experience using Git for version control.
• Basic knowledge of Docker, cloud platforms (AWS, GCP, or Azure), Linux environments, and MLOps fundamentals is a plus.
• Understanding of evaluation metrics such as accuracy, precision, recall, and F1-score.
• Exposure to LangChain, RAG pipelines, LLM application development, model optimization techniques, or participation in Kaggle or similar competitions is a plus.

Responsibilities:

• Assist in designing, developing, testing, and implementing machine learning and deep learning models for structured and unstructured data under senior guidance.
• Support NLP tasks, including text classification, basic named entity recognition (NER), chatbot features, and fine-tuning pre-trained and transformer-based models.
• Assist in building and maintaining Retrieval-Augmented Generation (RAG) pipelines and support LoRA-based fine-tuning when required.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis (EDA) to prepare datasets for training and evaluation.
• Conduct experiments, evaluate model performance using standard metrics, optimize basic hyperparameters, and document results.
• Assist in integrating large language model (LLM) APIs into applications and support prompt engineering and testing using frameworks such as LangChain or similar tools.
• Assist in deploying machine learning models using REST APIs (FastAPI or Flask), support Docker-based containerization, and contribute to CI/CD pipelines and version control using Git.
• Monitor model performance in staging and production and support dataset and model versioning.
• Assist in developing and evaluating computer vision models, including image classification, object detection, and segmentation, and support image preprocessing.
• Document code, models, and workflows, and collaborate with data engineers, backend developers, and product teams.
• Stay updated with machine learning, LLM, and AI advancements and continuously improve technical skills.