Posted:2 months ago| Platform:
Hybrid
Full Time
Must have: Gen AI, Agentic AI, Computer Vision, Tensorflow, Pytorch.. etc.. Proficiency in programming languages such as Python, with hands on experience in AIML libraries, Gen AI, Cloud ML, Vertex AI services and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of Gen AI, Agentic AI, Prompt engineering, AIML concepts, algorithms, and techniques. Experience with data preprocessing, feature engineering, and data visualization. Strong analytical and problem-solving skills, with the ability to analyze complex datasets and extract actionable insights. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience deploying AIML models in cloud environments. Knowledge of software development practices, version control systems (e.g., Git), and agile methodologies. Excellent communication and collaboration skills to work effectively in cross-functional teams. Strong organizational and time management skills, with the ability to prioritize and manage multiple projects simultaneously. Good to have handson experience with NLP projects Responsibilities: Design and develop AIML models, algorithms, and applications to solve complex business problems. Collaborate with data scientists and subject matter experts to understand business requirements and translate them into AIML solutions. Implement and optimize AIML algorithms and models using programming languages such as Python, R, or Java. Conduct data preprocessing, feature engineering, and data exploration to ensure the availability of high-quality data for training and evaluation. Evaluate and benchmark different AIML models, frameworks, and tools to identify the most suitable solutions for specific use cases. Train, validate, and fine-tune AIML models using various techniques such as deep learning, reinforcement learning, and natural language processing. Deploy AIML models in production environments, ensuring scalability, performance, and reliability. Collaborate with software engineers to integrate AIML solutions into existing applications or develop new applications. Stay up-to-date with the latest advancements in AIML technologies, research papers, and industry trends. Provide technical guidance and support to junior team members and promote knowledge sharing within the COE team.
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