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 (JR): 6 – 8 Areas

Actionable (4-6)

• 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

Key Skills :

• 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
• Strong analytical and problem-solving skills