Role Overview :
We are seeking a skilled Traditional AI Engineer with 5-7 years of experience to design, architect, and implement AI solutions independently. The role requires a strong foundation in data science and machine learning, with expertise in developing scalable AI models and algorithms tailored to industry-specific challenges.
Key Responsibilities :
- Design and implement end-to-end AI / ML solutions across domains, including predictive analytics and optimization.
- Build and deploy supervised, unsupervised, and reinforcement learning models.
- Lead rapid prototyping, experimentation, and PoC development.
- Manage full model lifecycle : data prep, feature engineering, training, evaluation, deployment, and monitoring.
- Collaborate with data engineers, MLOps, and product teams to operationalize models.
- Mentor junior engineers and uphold best practices in AI delivery.
- Stay current with emerging AI tools, frameworks, and methodologies.
Requirements :
5–7 years of hands-on experience in AI and data science.Proficient in Python, TensorFlow, PyTorch, or similar frameworks.Strong solution architecture and independent delivery capabilities.Excellent communication and mentoring skills.Proven deployment experience in healthcare, BFSI, or retail / CPG.Solid foundation in data modeling, feature engineering, and statistical analysis.Bachelor’s / Master’s in Computer Science, Data Science, or related field.Technical Skills & Tools :
Programming : Python (NumPy, Pandas, Scikit-learn), SQLFrameworks : TensorFlow, PyTorch, Keras, XGBoost, LightGBMCloud & Data Platforms : AWS SageMaker, Azure ML, GCP Vertex AI, DatabricksMLOps : MLflow, Kubeflow, Docker, Kubernetes, AirflowCI / CD & Version Control : GitHub, Jenkins, Azure DevOpsOther : Feature Engineering, Statistical Modeling, Explainability (SHAP, LIME), AI Ethics & Governance