AI/ML Engineer/Sr Engineer/Lead
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Job Location:
Monthly Salary:
Posted on:
18-09-2025
Vacancies:
1 Vacancy
Job Summary
AI/ML Engineer/Sr Engineer/Lead
Location: Kochi / Bangalore (initially in Kochi)
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:
oCI/CD for ML (GitHub Actions Azure DevOps etc.)
oModel versioning and registry (MLflow SageMaker Vertex AI etc.)
oData versioning (DVC LakeFS)
oMonitoring 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
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:
oCI/CD for ML (GitHub Actions Azure DevOps etc.)
oModel versioning and registry (MLflow SageMaker Vertex AI etc.)
oData versioning (DVC LakeFS)
oMonitoring 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)
Key Skills
- Administrative Skills
- Facilities Management
- Biotechnology
- Creative Production
- Design And Estimation
- Architecture
