Data Scientist (AI/ML)

TL;DR

Data Scientist (AI/ML): Designing, building, and evaluating models for NLP, document extraction, classification, and generative AI tasks with an accent on developing end-to-end ML pipelines and productionizing models. Focus on analyzing model behavior, optimizing performance in large-scale environments, and staying current with transformer-based architectures and LLMs.

Location: On-site in Pune, India

Company

hirify.global is a leader in autonomous spend-to-pay software, utilizing patented artificial intelligence to process information from thousands of data sources to help global enterprises understand and manage their spend.

What you will do

• Design, build, and evaluate models for NLP, document extraction, classification, and generative tasks.
• Develop end-to-end ML pipelines from data pre-processing to model inference and monitoring.
• Productionize models, including packaging, API integration, and deployment using Docker/Kubernetes.
• Analyze model behavior, debug Python code, and optimize performance in large-scale environments.
• Collaborate with product managers and engineering teams to translate business requirements into ML-driven product features.
• Stay current with research and advancements in transformer-based architectures, LLMs, and generative AI techniques.

Requirements

• 2–5 years of professional experience in Python, with strong debugging, profiling, and performance optimization skills.
• Solid understanding of Python data structures, algorithms, and software engineering best practices in ML development.
• Hands-on experience with NLP and modern ML frameworks like PyTorch, TensorFlow, or Hugging Face Transformers.
• Applied experience with transformer models, LLMs, or generative AI in real-world scenarios.
• Experience with model evaluation, including designing meaningful metrics, tracking model drift, and optimizing performance in production.
• B.E./ B.Tech or higher in Computer Science, Engineering, or a related technical field.

Nice to have

• Experience building and deploying containerized ML services with Docker and CI/CD pipelines.
• Skilled in designing and consuming RESTful Python APIs (e.g., FastAPI, Flask).
• Experience with cloud services, particularly AWS (S3, SQS, etc.).
• Familiarity with databases such as PostgreSQL and Redis.

Culture & Benefits

• Not explicitly mentioned in the provided job description.