AI/ML Developer - Application Integration & Workflows

Job Title : - AI/ML Developer - Application Integration & Workflow Development Job role : AI/ ML Developer Job type : Remote Shift : 8 PM to 5 AM Experience : 2 Years Benefits : Food allowance, Night shift allowance (as per process), Internet allowance, Health insurance, and many more Job Overview : The AI/ML Developer will play a critical role in supporting the AI Research Scientist by implementing and integrating AI models into production environments. This role focuses on developing robust workflows, automating deployment processes, and ensuring the seamless integration of AI models into applications. The developer will translate research into practical, high-impact AI solutions that align with business objectives. Key Responsibilities : 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 experimentation. - 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. Technical Skills : 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 SQL and NoSQL 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 Qualifications : 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. (ref:hirist.tech)

Location: in, IN

Posted Date: 11/21/2024