Must Have - Machine Learning and Statistical modeling, MS SQL, Python, PyTorch, TensorFlow
Job Details:
We are seeking an experienced AI Application Developer / AI Engineer to design, build, and deploy end to end AI solutions using modern machine learning and generative AI techniques. The role involves working hands on with data, models, and production systems to deliver scalable, reliable AI applications—without reliance on code assist tools such as GitHub Copilot.
Key Responsibilities
• Design, develop, and deploy end to end AI applications from data ingestion to production inference.
• Build data pipelines for data preparation, feature engineering, and model training.
• Select, train, evaluate, and optimize machine learning and deep learning models.
• Develop APIs and services to expose AI models for real time and batch use cases.
• Implement monitoring, logging, and model performance tracking in production.
• Collaborate with product, data, and domain teams to translate business requirements into AI solutions.
• Ensure AI solutions meet enterprise standards for security, scalability, and responsible AI usage.
Required AI Skill Areas (Core – 4 Skills)
1. Machine Learning & Model Development
• Strong understanding of supervised and unsupervised learning techniques.
• Familiarity with evaluation metrics and model validation techniques.
2. Data Engineering & Feature Engineering
• Hands on experience with data preprocessing, cleaning, and exploratory data analysis.
• Experience using Python libraries such as Pandas and NumPy, along with SQL.
3. Generative AI / LLM Based Application Development
• Experience building applications using Large Language Models (LLMs).
• Experience integrating LLM APIs into enterprise applications.
4. AI System Design, Deployment & MLOps
• Ability to design scalable AI architectures for training and inference.
• Experience deploying models as APIs or services (e.g., using FastAPI or Flask).
Technical Skills
• Strong proficiency in Python
• Experience with ML/DL frameworks such as PyTorch or TensorFlow
• Familiarity with REST APIs, microservices, and cloud platforms (GCP)
• Knowledge of model lifecycle management tools (e.g., MLflow – preferred)