Lead - AI/ML

Role & responsibilities

AI/ML Model Development: o Design, build, and deploy machine learning models and AI algorithms to address business challenges. o Develop and optimize deep learning models and algorithms to enhance performance and accuracy. o Implement algorithms for large-scale data processing and real-time analytics. • Deep Learning: o Design, implement, and optimize deep learning models for various applications, including classification, regression, and generative tasks. o Utilize frameworks such as TensorFlow and PyTorch to develop neural networks and advanced deep learning architectures. • Image Analytics: o Develop and deploy image recognition and analysis models to extract insights from visual data. o Apply convolutional neural networks (CNNs) and other image processing techniques to solve problems such as object detection, segmentation, and classification. • Video Analytics: o Implement video analysis solutions to process and interpret video data for tasks such as object tracking, action recognition, and anomaly detection. o Leverage deep learning techniques and tools for real-time video processing and analysis. • Voice Analytics: o Develop and deploy models for voice recognition, sentiment analysis, and speaker identification. o Use natural language processing (NLP) and audio signal processing techniques to analyze and interpret voice data. • Text Analytics: o Implement text mining and NLP techniques to extract valuable insights from unstructured text data. o Develop models for sentiment analysis, topic modeling, and text classification using state-of-the-art NLP frameworks. • Cloud & Infrastructure: o Utilize cloud platforms such as AWS and Azure for deploying and managing AI/ML models and infrastructure. o Leverage cloud-based tools and services, including Amazon SageMaker, Azure Machine Learning, and Azure Databricks, for model development and deployment. • Integration & Deployment: o Integrate AI/ML models into existing systems and workflows to ensure seamless operation. o Develop APIs and interfaces for model interaction and integration with applications. • Performance Monitoring: o Monitor and evaluate the performance of AI/ML models and systems to ensure they meet business objectives. o Continuously refine and optimize models based on performance data and feedback. • Collaboration: o Work closely with data scientists, business analysts, and other stakeholders to understand requirements and develop technical solutions. o Collaborate with cross-functional teams to implement and optimize AI/ML solutions. • Documentation & Reporting: o Maintain comprehensive documentation for AI/ML models, algorithms, and deployment processes. o Communicate technical findings and progress to stakeholders clearly and effectively. • Innovation & Best Practices: o Stay updated with the latest advancements in AI/ML technologies and techniques. o Explore and implement new tools and methods to enhance AI/ML capabilities and solutions.

Preferred candidate profile

Experience: o 7-9 years of hands-on industry experience in AI/ML engineering, including work with deep learning, image analytics, video analytics, voice analytics, and text analytics. o Proven track record of deploying machine learning models in production environments. o Hands on experience on implementation of different type of machine learning algorithms such as supervised, semi-supervised, unsupervised and reinforcement. o Hands on experience on implementation of LLM Models & Generative AI. • Technical Skills: o Proficiency in programming languages such as Python, R, or Java. o Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). o Strong understanding of deep learning, image processing, video analytics, and NLP techniques. • Cloud Skills: o Hands-on experience with cloud platforms like AWS and Azure, including:  AWS: Amazon SageMaker, AWS Lambda, AWS Glue, Amazon Redshift.  Azure: Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, Azure Cognitive Services. • Data Tools: o Experience with data visualization tools like Power BI, Tableau, or similar. o Familiarity with big data technologies and data storage solutions is a plus. • Soft Skills: o Strong analytical and problem-solving skills with attention to detail. o Excellent communication and interpersonal skills. o Ability to manage multiple projects and work in a fast-paced environment. • Educational Background: Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a related field with substantial experience in AI/ML engineering