AI Engineer

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Experience: 5+ yrs

Location: Bengaluru, Karnataka, India

As a AI Engineer, you will spearhead the development and deployment of cutting-edge artificial intelligence solutions that drive business value for complex, data-rich environments. You will design, implement, and optimise machine learning pipelines, leveraging advanced generative AI techniques and ensuring scalability across cloud platforms. Your work will involve close collaboration with data scientists, product managers, and domain experts to translate business challenges into robust AI models that are both performant and auditable. With a strong foundation in Python and deep expertise in MCP frameworks, you will continuously iterate on model performance and integrate new AI capabilities into existing systems, while maintaining high standards of code quality and documentation.

Requirements

• Design and develop end-to-end AI solutions using Python, TensorFlow/PyTorch, and MCP tools.
• Build and maintain scalable machine learning pipelines that support real-time inference and batch processing.
• Integrate generative AI models (e.g., GPT, Stable Diffusion) into product workflows to enhance user experience and content creation.
• Conduct rigorous model validation, testing, and performance evaluation to ensure reliability and compliance with industry standards.
• Optimize models for latency, throughput, and resource utilization across on-premise and cloud infrastructures.
• Work closely with data engineering teams to curate high-quality datasets and implement data ingestion workflows.
• Collaborate with software engineers to embed AI services into microservices architectures and RESTful APIs.
• Monitor deployed models for drift, accuracy, and ethical considerations, implementing retraining pipelines as needed.
• Lead code reviews and mentor junior engineers on best practices in AI development and deployment.
• Stay abreast of the latest research in generative AI and MCP, translating cutting-edge findings into practical solutions.
• 5+ years of professional experience in AI/Machine Learning engineering roles.
• Proven expertise in Python, including advanced libraries such as NumPy, Pandas, Scikit-Learn, and deep learning frameworks.
• Hands-on experience with MCP (Model Compression and Pruning) techniques for deploying models on edge and low-latency environments.
• Strong background in designing, training, and fine-tuning generative AI models like GPT, BERT, and Diffusion models.
• Demonstrated ability to deploy AI solutions at scale using Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure).
• Excellent problem-solving skills with a track record of delivering robust, production-ready AI systems.
• Ability to translate complex technical concepts into clear, actionable insights for cross-functional teams.
• Strong communication skills, comfortable presenting findings to both technical and non-technical stakeholders.
• Experience with CI/CD pipelines and automated testing frameworks for AI models.
• A passion for continuous learning, staying updated on emerging AI research and industry best practices.