Artificial Intelligence/Machine Learning Engineer - NLP

Description : Hiring for AI Engineer for Product based company. Location : Gurugram/Pune. Work Mode : Hybrid. Exp : 3+ Years. Domain Experience : Healthcare.

What you will bring :

- Bachelor's degree completed in Computer Science or a related field.

- 3+ years of experience with AI, software engineering, MLOps, DevOps, or data engineering, in a professional role.

- Experience with document intelligence, generative AI, agentic AI, automation, NLP and machine learning.

- Experience with Azure DevOps, CI/CD, Terraform, Python and other scripting languages.

- Experience with integrating DevSecOps practices and principles throughout the project life cycle.

- Experience with Big Data technologies, cloud-based analytics, non-relational datastores, data visualization tools, and open-source tools for data processing.

- Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira.

What we would like to see :

- Experience with Databricks and Azure cloud platforms, machine learning services, and best practices.

- Experience in open-source AI/ML tools, frameworks technologies (for example, Meta, HuggingFace, Nemo, TensorFlow, PyTorch, scikit-learn, Apache MXnet, Spark MLlib, etc.).

- Experience with predictive analytics in Healthcare, Insurance or Consumer Credit industry.

Key Responsibilities :

- Design, develop, and deploy AI and ML solutions across multiple product lines.

- Work on document intelligence, NLP, generative AI, and agentic AI solutions to enhance automation and decision-making capabilities.

- Collaborate with data engineers and DevOps teams to implement MLOps pipelines for model deployment, monitoring, and retraining.

- Integrate DevSecOps principles and CI/CD pipelines using Azure DevOps and Terraform.

- Build and maintain cloud-based data pipelines using big data technologies and non-relational databases.

- Collaborate with product managers and stakeholders to understand healthcare-specific data and translate it into actionable insights.

- Implement AI governance, security, and compliance standards within the healthcare ecosystem.

- Utilize Agile methodologies (Scrum/Kanban) to manage sprint deliverables and project timelines.