Data Scientist

Join AppZen's expanding AI/ML team as an experienced Data Scientist with robust Python skills. Collaborate with a distinguished group of machine learning engineers and scientists on pioneering NLP, document understanding, and enterprise automation initiatives.

Key Responsibilities:

• Design, develop, and assess models for Natural Language Processing (NLP), document extraction, classification, and generative tasks.
• Build comprehensive machine learning (ML) pipelines, covering data preprocessing, model inference, and ongoing monitoring.
• Contribute to the productionization of models, including packaging, API integration, and deployment using technologies like Docker and Kubernetes.
• Analyze model performance, debug Python code, and optimize for efficiency in large-scale environments.
• Transform prototypes into reliable, production-ready ML services, prioritizing performance and stability.
• Enhance model and system monitoring, logging, and performance optimization efforts.
• Partner with product managers and engineering teams to translate business needs into ML-powered product features.
• Stay abreast of the latest research and advancements in transformer architectures, Large Language Models (LLMs) such as GPT and BERT, and generative AI methodologies.

Required Qualifications:

• 2–5 years of professional Python experience, including strong capabilities in debugging, profiling, and performance optimization.
• A firm understanding of Python data structures, algorithms, and software engineering best practices in ML development.
• Practical experience with NLP and modern ML frameworks like PyTorch, TensorFlow, or Hugging Face Transformers.
• Demonstrated application of transformer models, LLMs, or generative AI in real-world projects.
• Experience in model evaluation, including defining key metrics, tracking model drift, and optimizing production performance.
• Aptitude for managing multiple priorities within a dynamic and collaborative setting.
• Bachelor of Engineering (B.E.)/Bachelor of Technology (B.Tech) or higher in Computer Science, Engineering, or a related technical discipline.

Preferred Qualifications:

• Experience in developing and deploying containerized ML services using Docker and CI/CD pipelines.
• Proficiency in designing and utilizing RESTful Python APIs (e.g., FastAPI, Flask).
• Experience with cloud platforms, particularly AWS (e.g., S3, SQS).
• Familiarity with databases such as PostgreSQL and Redis.
• Solid knowledge of classical ML algorithms like Logistic Regression, Random Forests, and XGBoost.
• The ability to pragmatically select between heuristic, rule-based, and model-driven solutions (e.g., regex versus ML).