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Artificial Intelligence Engineer - NLP/Machine Learning

Velodata Global Pvt Ltd
Multiple Locations
4 - 7 Years

Posted on: 19/09/2025

Job Description

About the job :

AI/ML Engineer/Sr Engineer/Lead

Location : Kochi / Bangalore (initially in Kochi)

Role Summary :

We are looking for a hands-on AI/ML Engineer to design, build, and deploy production-grade machine learning systems. The role requires strong experience in both model development and MLOps practices, ensuring that ML solutions are scalable, maintainable, and performance optimized.

Key Responsibilities :

- Design and implement ML models for classification, regression, clustering, Recommendation System, Anomaly Detection, Neural Networks, NLP, Comp Vision Models

- Package models and deploy them into production environments using CI/CD workflows

- Develop and manage ML pipelines for data preprocessing, training, testing, and serving

- Monitor model performance in production (latency, drift, accuracy) and retrain when needed

- Collaborate with data engineers, MLOps engineers, and DevOps to ensure smooth deployments

- Support versioning of models, datasets, and configurations

- Participate in performance tuning, experiment tracking, and governance enforcement

Must-Have Skills :

- Strong programming skills in Python, with experience in Scikit-learn, XGBoost, or TensorFlow/PyTorch

- Experience building and deploying models using Flask, FastAPI, or Streamlit

- Solid grasp of MLOps concepts :

1. CI/CD for ML (GitHub Actions, Azure DevOps, etc.)

2. Model versioning and registry (MLflow, SageMaker, Vertex AI, etc.)

3. Data versioning (DVC, LakeFS)

4. Monitoring and retraining workflows

- Comfortable working with containerization (Docker) and deployment on cloud platforms (AWS, Azure, or GCP)

- Good understanding of model explainability, fairness, and data privacy

Nice to Have :

- Familiarity with Airflow, Kubeflow, or Prefect for orchestration

- Exposure to feature stores and drift detection tools

- Experience with NLP (LLMs, Transformers) or time series forecasting

- Understanding of model caching, load testing, and API security for ML services

- Domain Knowledge in Financial Services (especially Capital Markets)


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