AI Developer

2 days ago

Noida, Uttar Pradesh, India Infopro Learning Full time ₹ 15,00,000 - ₹ 20,00,000 per year

We are looking for an experienced and results-driven AI Developer to join our team. The ideal candidate will be responsible for developing, deploying, and optimizing AI and machine learning models to solve real-world business problems. You will collaborate with cross-functional teams to deliver scalable and ethical AI solutions using state-of-the-art tools and technologies.

Key Responsibilities

Data Engineering & Preprocessing

  • Collaborate with data scientists and engineers to source, clean, and preprocess large datasets.

  • Perform feature engineering and data selection to improve model inputs.

AI Model Development & Implementation

  • Design, build, and validate machine learning and deep learning models, including:

    • Convolutional Neural Networks (CNNs)

    • Recurrent Neural Networks (RNNs/LSTMs)

    • Transformers

    • NLP and computer vision models

    • Reinforcement learning agents

    • Classical ML techniques

  • Develop models tailored to domain-specific business challenges.

Performance Optimization & Scalability

  • Optimize models for performance, latency, scalability, and resource efficiency.

  • Ensure models are production-ready for real-time applications.

Deployment, MLOps & Integration

  • Build and maintain MLOps pipelines for model deployment, monitoring, and retraining.

  • Use Docker, Kubernetes, and CI/CD tools for containerization and orchestration.

  • Deploy models on cloud platforms (AWS, Azure, GCP) or on-premise infrastructure.

  • Integrate models into systems and applications via APIs or model-serving frameworks.

Testing, Validation & Continuous Improvement

  • Implement testing strategies like unit testing, regression testing, and A/B testing.

  • Continuously improve models based on user feedback and performance metrics.

Research & Innovation

  • Stay up to date with AI/ML advancements, tools, and techniques.

  • Experiment with new approaches to drive innovation and competitive advantage.

Collaboration & Communication

  • Work closely with engineers, product managers, and subject matter experts.

  • Document model architecture, training processes, and experimental findings.

  • Communicate complex technical topics to non-technical stakeholders clearly.

Ethical AI Practices

  • Support and implement ethical AI practices focusing on fairness, transparency, and accountability.

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