About the job
AI Developer - Transformative Solutions in Noida
Position Type: Full-time Employee
Location: Onsite - Noida, India
Why This Role Exists
At InfoPro Learning, we are committed to developing AI solutions that address genuine business challenges rather than mere prototypes or academic exercises. As an AI Developer, you will play a critical role in designing, developing, deploying, and enhancing production-grade AI and machine learning systems that make a tangible impact. This opportunity is ideal for individuals who thrive on hands-on development, prioritize quality and scalability, and are eager to witness their ideas materialize into meaningful change.
This is a full-time, onsite position based in our Noida office. You will collaborate with engineers, data scientists, and product partners in a dynamic and fast-paced environment.
What You Will Do
Build and Deliver AI Solutions
Design, develop, and validate machine learning and deep learning models to tackle domain-specific business issues.
Utilize a variety of methodologies, including classical ML, NLP, computer vision, reinforcement learning, and transformer-based models.
Implement Generative AI techniques, working with large language models and retrieval-based systems as necessary.
Data Engineering and Preparation
Collaborate with data scientists and engineers to source, clean, and preprocess extensive datasets.
Engage in feature engineering and data selection to enhance model inputs and outcomes.
Production Deployment and MLOps
Deploy models into production environments for real-time or near real-time applications.
Develop and maintain MLOps pipelines for deployment, monitoring, versioning, and retraining processes.
Utilize Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS, Azure, or GCP.
Integrate models into applications using APIs or model-serving frameworks.
Performance, Quality, and Improvement
Optimize models for performance, latency, scalability, and resource efficiency.
Develop testing strategies, including unit testing, regression testing, and A/B testing.
Monitor model performance and iteratively enhance solutions based on analytics, user feedback, and usage patterns.
Collaboration and Communication
Work closely with cross-functional teams comprising engineers, product managers, and subject matter experts.
Document model architectures, training methodologies, and experimental results thoroughly.
Effectively communicate technical concepts to both technical and non-technical stakeholders.
Ethical and Responsible AI
Contribute to the organization's commitment to developing ethical AI solutions that are fair and transparent.
