Conduct experimentation, hyperparameter tuning, and A/B testing
AI Application Development
Integrate AI models into applications via APIs and microservices
Build AI-powered features such as:
Recommendation systems
Chatbots and virtual assistants
Computer vision and NLP solutions
Collaborate with backend and frontend teams for seamless integration
Deployment & MLOps
Deploy models using Docker, Kubernetes, or cloud AI services
Implement CI/CD pipelines for ML workflows
Monitor model performance, drift, and reliability in production
Cloud & Platform Usage
Use cloud AI platforms such as AWS, Azure, or Google Cloud
Work with services like SageMaker, Vertex AI, Azure ML
Optimize compute, storage, and inference costs
Security, Ethics & Compliance
Ensure responsible AI practices (bias detection, explainability, fairness)
Secure models, data, and APIs
Follow data privacy and regulatory guidelines (GDPR, HIPAA, etc.)
Testing & Debugging
Validate data pipelines and model outputs
Debug training and inference issues
Perform performance optimization and scalability testing
Documentation & Collaboration
Document models, data sources, and decision logic
Collaborate with data scientists, product managers, and engineers
Communicate technical results to non-technical stakeholders
Optional / Advanced Responsibilities
Research and implement state-of-the-art AI techniques
Build custom ML frameworks or libraries
Mentor junior AI/ML engineers
Drive AI strategy and innovation initiatives
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or a related field
Proven experience as an AI Developer, ML Engineer, or similar role
Strong programming skills in Python (experience with Java/Scala is a plus)
Hands-on experience with machine learning and deep learning frameworks Like TensorFlow, PyTorch, Scikit-learn
Solid understanding of ML algorithms, statistics, and model evaluation techniques
Experience with data preprocessing, feature engineering, and large datasets
Knowledge of MLOps practices, model deployment, and monitoring
Experience with Docker, Kubernetes, and CI/CD pipelines
Familiarity with cloud platforms (AWS, Azure, GCP) and AI services
Understanding of AI ethics, security, and compliance standards
Strong problem-solving, analytical, and communication skills
Ability to work effectively in cross-functional teams
Common Skills & Tools
Languages: Python, R, Java
Frameworks: TensorFlow, PyTorch, Scikit-learn
Data: SQL, NoSQL, Pandas, Spark
MLOps: MLflow, Kubeflow, Airflow
Cloud: AWS, Azure, GCP
Educational Qualification
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field
We offer a professional work environment and are given every opportunity to grow in the Information technology world.
Note
Candidates are required to attend Phone/Video Call / In-person interviews and after Selection of candidate (He/She) should go through all background checks on Education and Experience.
Please email your resume to: keshini@petadata.co
After carefully reviewing your experience and skills one of our HR team members will contact you on the next steps.