• Remote job opportunity
• Internet allowance
• Canteen Subsidy
• Night Shift allowance as per process
• Health Insurance
• Tuition Reimbursement
• Work Life Balance Initiatives
• Rewards & Recognition
• Internal movement through IJP

WHAT YOU’LL BE DOING: 

Model Integration & Deployment: 

• Collaborate with the AI Research Scientist to implement and deploy AI models, particularly those developed for NLP, computer vision, and audio processing. 
• Utilize AWS Sagemaker and developed model weights for efficient deployment. 
• Understanding of how AI systems work to properly understand needed aspects for proper AI/ML implementation and experiementation. 
• Properly construct needed inputs for model inference and handle model output to bridge between analysis and application use. 

Workflow Development & Automation: 

• Design and develop robust data workflows and automate processes for model deployment. 
• Build repeatable procedures and processes for training, validation, and testing of models. 

Software Development & Integration: 

• Develop software components for integrating AI models into user-facing applications. 
• Implement a system that allows for release cycles to update aspects of the AI/ML development cycle. 

Data Engineering Support: 

• A strong ability to work with data transformation needs to help provide access for model development. 
• Understanding of how to optimize data transformations at scale. 

Collaboration & Documentation: 

•  Document processes and collaborate closely with other AI team members to ensure smooth integration and deployment. 

WHAT WE EXPECT YOU TO HAVE: 

Programming Languages: 

• Python: Advanced proficiency in Python, particularly for integrating AI models into applications, automating workflows, and handling data processing tasks. 
• JavaScript/TypeScript: Proficiency in JavaScript or TypeScript for developing and integrating frontend components that interact with AI models. 
• Software Development & Integration: 
• API Development: Experience in developing RESTful APIs and microservices that enable AI models to interact with applications and other systems. 
• Containerization & Orchestration: Proficiency in using Docker and Kubernetes for containerizing AI applications and managing scalable deployments. 
• Frontend Integration: Ability to integrate AI models into frontend applications, ensuring smooth data flow and user interaction. 

Data Engineering Skills:

• Data Transformation & Processing: Strong understanding of data transformation techniques, including ETL processes, data normalization, and handling large-scale data in distributed systems. 
• Database Management: Experience with both SǪL and NoSǪL databases, particularly in optimizing queries and data structures for AI/ML tasks. 
• Data Pipeline Development: Ability to design and implement data pipelines that facilitate seamless data flow from raw data to model-ready datasets. 

Experience: 

• Model Integration & Deployment: Proven experience in deploying AI models into production environments, ensuring that they are scalable, efficient, and reliable. 
• Workflow Automation: Demonstrated ability in automating workflows for model training, validation, testing, and deployment, ensuring repeatability and consistency across development cycles. 
• Software Development Lifecycle: Strong experience in the full software development lifecycle (SDLC), including requirements gathering, design, coding, testing, deployment, and maintenance. 
• Cross-functional Collaboration: Experience working in cross-functional teams, including collaboration with data scientists, AI researchers, and software engineers to integrate AI solutions into production systems. 

Education: 

• Academic Ǫualifications: Bachelor’s degree in Computer Science, Software Engineering, or a related field. An advanced degree or relevant certifications in AI/ML or software development would be an advantage. 
• Certifications: Relevant certifications in cloud computing (e.g., AWS Certified Solutions Architect), software development (e.g., Certified Kubernetes Administrator), or AI/ML (e.g., TensorFlow Developer) are a plus. 

Other Skills: 

• Problem-Solving: Strong analytical skills with the ability to troubleshoot and resolve complex infrastructure and deployment issues in a timely manner. 
• Collaboration: Ability to work closely with AI Team and developers to understand infrastructure needs and provide robust technical support. 
• Documentation: Experience in creating clear, detailed documentation for infrastructure setups, deployment pipelines, and operational procedures to facilitate knowledge sharing and reproducibility.