Lead Platform Architect (AI Architect)

Job Purpose

An experienced AI/ML Engineer to design, develop and maintain AI / ML and GenAI based solutions on enterprise platform on Industry best and open-source models at scale along with governance and security frameworks

Job Responsibilities -

Design and implement the necessary infrastructure (e.g., compute clusters, storage, networking) for AI applications, including cloud platforms like AWS, Azure, or GCP

Design, build, and train generative AI models using techniques like deep learning and neural networks

Develop and maintain scalable, efficient, and reliable data pipelines for AI models, ensuring data quality and integrity.

Integrate machine learning models into AI platforms and deploy them into production environments, often using AIOps, MLOps and LLMOps frameworks

Design and implement monitoring strategies for AI platforms and optimize their performance for scalability and real-time applications.

Perform machine learning tests and statistical analysis to fine-tune the machine learning systems

Work with the engineering and leadership teams on the functional design, process design, prototyping, testing, performance evaluation and training of AI/ML solutions Extend existing machine learning libraries and frameworks

Implemented and evaluated machine learning models, including supervised, unsupervised, and reinforcement learning techniques, for B2C use cases

Strong experience with deep learning frameworks like TensorFlow and PyTorch

Used Python or other programming models to build and train a deep learning model for Document Classification, Extraction, Signature matching, STT, TTS kind of use cases

Demonstrated ability to fine-tune and optimize models using large data sets

Certified in AI/ML in any of the cloud platforms like AWS, Azure, or GCP and experience deploying AI/ML models in the cloud

Effective communication skills, both written and verbal, with the ability to effectively communicate technical concepts to non-technical audiences

Educational Qualifications (examples listed below) Key Skills (examples listed below)

Graduation: Master's degree in a relevant technology field

Certifications: Any Cloud Certifications with AI/ML Strong background in designing and implementing machine learning and deep learning algorithms and responsible AI practices at enterprise scale and speed

Working knowledge with ML platforms like TensorFlow, PyTorch, or Hugging Face

Proficiency in Training, Tuning and Deploying GenAI models based on LLMs, GANs, and VAEs

Hands on expert in programming languages like Python, Java, or C++, and have experience with cloud platforms, containerization technologies (e.g., Docker, Kubernetes), and data pipeline tools (e.g., Apache Kafka, Spark)

Experience working in cross-functional teams

Experience Required

11-15 years, Location -Bangalore.