Role Overview
We are seeking a Data Scientist with a strong engineering background to design, build, train, and operationalize machine learning models that deliver measurable business impact. You will work end-to-end across feature engineering, model training, inference, and post-processing, leveraging a up-to-date, cloud-native ML platform built on GCP and Kubernetes. This role blends strong statistical and machine learning expertise with hands-on MLOps practices, ensuring models are reliable, scalable, and production-ready.

Key ResponsibilitiesModel Development & Data Science

- Develop, train, and validate machine learning models using Python
- Perform feature engineering, exploratory data analysis, and model evaluation.
- Apply appropriate ML techniques for prediction, classification, or optimization use cases. ML Workflow Orchestration
- Use Argo Workflows on Kubernetes to orchestrate model inference and post-processing pipelines.
- Design repeatable, automated workflows for ML experiments and production inference. Model Training & Validation
- Leverage Vertex AI to run scalable model training, hyperparameter tuning, and validation.
- Ensure reproducibility and consistency across training runs. Model Runtime & Inference
- Build and maintain Python-based runtimes for training, inference, and feature engineering.
- Optimize inference pipelines for performance, reliability, and scalability.
- Handle and monitor pipelines in production environments.




- Participate in Oncall rotation for inference infrastructure. Model Storage & Lifecycle Management
- Handle trained artifacts in Google Cloud Storage (GCS).
- Track model metadata, versions, and lineage using Argo or custom model registries.
- Support model versioning, rollback, and auditability..Quality, Monitoring & Governance
- Define model evaluation metrics and validation criteria.
- Support post-deployment monitoring, drift detection, and retraining strategies.
- Follow best practices for documentation, testing, and responsible AI usage.Required Skills & Qualifications Technical Skills
- Strong on-hands proficiency in Python for data science and machine learning use-cases.
- Hands-on experience with ML frameworks (e.g., PyTorch, scikit-learn, catboost, …).
- Familiarity with Kubernetes and Kubernetes-based workflows, especially Argo Workflows.

Data Science & ML Concepts

- Strong understanding of feature engineering, model evaluation, and validation techniques.
- Experience taking models from experimentation to production inference.
- Understanding of ML lifecycle management and MLOps principles. Soft Skills
- Strong analytical and problem-solving mindset.
- Ability to translate business problems into data science solutions.
- Clear communication skills to explain models and results to diverse stakeholders.

Pay: ₹500,000.00 - ₹1,400,000.00 per year

Benefits:

- Health insurance
- Life insurance
- Provident Fund

Work Location: In person

📌 Data Scientist (Hyderabad)
🏢 AVISOFT
📍 Hyderabad