AI Developer

AI Developer | Onsite, Noida | Open to India-based candidates only

Position type: Full-time employee

Location: Onsite - Noida, India

Why this role exists

We are building AI solutions that solve real business problems, not demos or experiments that live on a slide. As an AI Developer on our team, you will design, build, deploy, and continuously improve production-ready AI and machine learning systems used by real users. This role is for someone who enjoys hands-on development, cares about quality and scalability, and wants to see their work move from idea to impact.

This is a full-time, onsite role based in our Noida office. You will work closely with engineers, data scientists, and product partners in a collaborative, fast-moving environment.

What you will do

Build and deliver AI solutions

• Design, develop, and validate machine learning and deep learning models to address domain-specific business challenges
• Work across a range of approaches including classical ML, NLP, computer vision, reinforcement learning, and transformer-based models
• Apply Generative AI techniques, including working with large language models and retrieval-based systems, where appropriate

Data engineering and preparation

• Collaborate with data scientists and engineers to source, clean, and preprocess large datasets
• Perform feature engineering and data selection to improve model inputs and outcomes

Production deployment and MLOps

• Deploy models into production environments that support real-time or near real-time use cases
• Build and maintain MLOps pipelines for deployment, monitoring, versioning, and retraining
• Use Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS, Azure, or GCP
• Integrate models into applications through APIs or model-serving frameworks

Performance, quality, and improvement

• Optimize models for performance, latency, scalability, and resource efficiency
• Implement testing strategies including unit testing, regression testing, and A/B testing
• Monitor model performance and improve solutions based on data, feedback, and usage patterns

Collaboration and communication

• Work closely with cross-functional teams including engineering, product, and subject matter experts
• Document model architectures, training processes, and experimental results
• Communicate technical concepts clearly to both technical and non-technical stakeholders

Ethical and responsible AI

• Contribute to ethical AI practices with attention to fairness, transparency, and accountability
• Help identify and mitigate risks such as bias, hallucinations, or incorrect outputs