Location : Remote / Pune

Job Type : Full-Time

Shift Timing : 2 : 00 PM - 11 : 00 PM

Job Overview :

We are seeking an experienced AI/ML Engineer to develop, deploy, and maintain production-ready machine learning and NLP solutions. The role involves integrating AI/ML models into data pipelines and microservices, building model-serving workflows, and enabling continuous model training and monitoring.

Key Responsibilities :

- Develop, deploy, and maintain machine learning models and AI-powered services in production environments.

- Build NLP pipelines to process structured and unstructured data, including healthcare claims and clinical documents.

- Integrate ML models with data pipelines and backend services using REST APIs, GraphQL, or gRPC.

- Develop data preprocessing, feature engineering, model inference, and evaluation workflows.

- Implement model deployment and serving using Vertex AI Endpoints, TensorFlow Serving, or equivalent platforms.

- Build and manage model training, retraining, and orchestration workflows using Vertex AI, Kubeflow, or similar tools.

- Collaborate with Data Engineering, MLOps, and Platform teams to operationalize models.

- Implement model monitoring, prediction logging, confidence-score tracking, and fallback mechanisms.

- Optimize model performance, reliability, scalability, and inference latency.

- Explore GenAI and LLM-based solutions, prompt workflows, and agent orchestration frameworks where applicable.

Required Qualifications :

- 4 - 6 years of experience in AI/ML engineering, machine learning development, or production ML systems.

- Strong programming skills in Python.

- Hands-on experience deploying and integrating AI/ML models into production applications.

- Experience with NLP, text processing, or machine learning workflows.

- Understanding of the end-to-end ML lifecycle, including data preparation, feature engineering, training, deployment, and inference.

- Experience building or integrating REST APIs and working with backend services.

- Familiarity with structured and unstructured datasets.

- Experience with cloud platforms, preferably GCP.

- Understanding of model monitoring, evaluation, versioning, and performance optimization.

Preferred Qualifications :

- Experience with Vertex AI, Kubeflow, TensorFlow Serving, or equivalent ML platforms.

- Exposure to healthcare analytics, claims processing, or clinical NLP.

- Familiarity with BigQuery, Kafka, and cloud-based data pipelines.

- Experience with Docker, Kubernetes, and CI/CD workflows.

- Knowledge of GenAI, LLMs, LangChain, Hugging Face Transformers, or agent orchestration frameworks.

- Exposure to MLOps practices and automated model retraining.

Education :

- Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience