Aurigene Pharmaceutical Services - Artificial Intelligence/Machine Learning Specialist

Key Responsibilities

• Design, develop, and optimize machine learning and deep learning models for a variety of use cases.
• Collect, preprocess, and analyze structured and unstructured datasets to prepare them for model training.
• Select appropriate algorithms and techniques based on problem requirements and business objectives.
• Build end-to-end AI/ML pipelines including data ingestion, feature engineering, model training, evaluation, and deployment.
• Implement and optimize models using frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.
• Deploy models into production environments using cloud platforms (AWS SageMaker, Azure ML, GCP AI Platform) or on-premises solutions.
• Monitor, maintain, and retrain models to ensure long-term accuracy and performance.
• Collaborate with cross-functional teams (data engineers, software developers, domain experts) to integrate AI/ML solutions into products and workflows.
• Stay updated with the latest advancements in AI, ML, NLP, and computer vision to drive innovation.
  

Required Technical Skills

• Strong programming skills in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
• Solid understanding of ML algorithms (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers).
• Experience with NLP frameworks (Hugging Face, SpaCy, NLTK) and/or Computer Vision libraries (OpenCV, YOLO, Detectron).
• Proficiency in data wrangling and feature engineering for high-quality datasets.
• Knowledge of model deployment strategies using APIs, containers (Docker), and orchestration tools (Kubernetes).
• Familiarity with big data tools (Spark, Hadoop) for large-scale data processing.
• Understanding of MLOps practices, CI/CD pipelines, and model monitoring tools.
  

Preferred Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field.
• Experience in domain-specific AI (healthcare, finance, manufacturing, etc.
• Exposure to generative AI models (LLMs, Stable Diffusion, GPT-based systems).
• Understanding of data privacy and AI ethics.
  

Key Attributes

• Strong problem-solving and analytical skills.
• Excellent communication and presentation abilities.
• Ability to work collaboratively in cross-functional teams.
• Passion for continuous learning and innovation