AI Engineer
5 hours ago
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), SQL
- Frameworks: TensorFlow, PyTorch, Keras, XGBoost, LightGBM
- Cloud & Data Platforms: AWS SageMaker, Azure ML, GCP Vertex AI, Databricks
- MLOps: MLflow, Kubeflow, Docker, Kubernetes, Airflow
- CI/CD & Version Control: GitHub, Jenkins, Azure DevOps
- Other: Feature Engineering, Statistical Modeling, Explainability (SHAP, LIME), AI Ethics & Governance
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