AI Data Scientist

Job Description: AI Data Scientist & Annotation

Expert Position: AI Data Scientist & Annotation Expert

Location: [On-site], Plaza 118, Civic Center, Bahria Town Rawalpindi

Shift: Night shift (2am-11am)

Employment Type: Full-time

Salary Range: (PKR 200k-400k)

About the Role

We are looking for a skilled AI Data Scientist & Annotation Expert to drive the full lifecycle of AI/ML solutions — from data collection and annotation through advanced model development, training, and deployment.

The role combines hands-on annotation expertise (critical for building high-quality training datasets) with data science and machine learning skills to ensure robust, production-ready AI systems.

You will play a central role in curating high-quality datasets, experimenting with algorithms, and ensuring model performance by leveraging both advanced data science techniques and precise annotation workflows.

Key Responsibilities

Data Science & Machine Learning

• Design, build, and evaluate machine learning/deep learning models for NLP, Computer Vision, or multimodal tasks.

• Perform feature engineering, exploratory data analysis (EDA), and statistical modeling.

• Experiment with different model architectures (CNNs, RNNs, Transformers, LLMs) and optimize hyperparameters for maximum performance.

• Develop and deploy scalable ML pipelines in production (using FastAPI, TensorFlow Serving, TorchServe, or containerized environments).

• Collaborate with engineers and product teams to integrate models into end-user applications. Data Annotation & Curation

• Design annotation workflows and guidelines for various data types (images, PDFs, audio, video, and text).

• Perform and manage manual and semi-automated annotation tasks (e.g., bounding boxes, polygons, segmentation masks, labeling, and text tagging).

• Implement quality control measures to ensure annotations meet accuracy and consistency standards.

• Train and supervise annotation teams, providing feedback and ensuring adherence to project requirements.

• Work with annotation tools (e.g., Label Studio, CVAT, Supervisely, Prodigy, Labelbox).

• Assist in building gold-standard datasets that serve as the foundation for AI/ML training. MLOps & Data Ops

• Set up pipelines for dataset versioning, experiment tracking, and model reproducibility (using MLflow, DVC, or similar).

• Monitor dataset drift, class imbalances, and annotation consistency to avoid bias in models.

• Collaborate with DevOps teams for deployment, scaling, and monitoring of AI models.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field.

• Strong programming skills in Python and familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).

• Solid understanding of machine learning algorithms, deep learning architectures, and statistical methods.

• 5 Years + Hands-on experience with data annotation platforms (Label Studio, CVAT, or similar).

• Familiarity with SQL/NoSQL databases and big data handling.

• Strong understanding of data preprocessing (cleaning, augmentation, normalization, and transformation).

Preferred Skills

• Prior experience in annotation team management or data labeling quality assurance.

• Knowledge of vector databases (pgvector, Pinecone, Weaviate, Chroma) for AI-driven search and RAG pipelines.

• Experience with MLOps tools (Airflow, Kubeflow, MLflow).

• Knowledge of annotation automation using weak supervision, active learning, or semi supervised learning techniques.

• Understanding of ethical AI practices, bias detection, and responsible dataset curation.

Soft Skills

• Exceptional attention to detail and accuracy in handling data.

• Ability to train, mentor, and guide annotation teams.

• Strong analytical and problem-solving skills.

• Effective communication for both technical and non-technical audiences.

• Self-driven, proactive, and collaborative mindset.