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Reputable employer and popular AI managerial title but specialized GenAI tooling keeps applicant density moderate.
Generative AI and ML skills transfer across industries but favor candidates with ML/AI-focused backgrounds.
Numerous mandatory GenAI, ML, cloud, and tooling requirements raise filtering rigidity.
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Lead design, development, and deployment of machine learning, deep learning, and generative AI models on cloud platforms (AWS, GCP, Azure).
Analyze data to generate actionable insights and improve reporting and analysis practices strategically beyond stop-gap measures.
Collaborate with cross-functional teams to integrate generative AI into products and services while ensuring ethical AI use.
Proficient in Python, SQL, and use of frameworks like Langchain for AI model development.
Experience deploying AI/ML models on cloud platforms such as AWS, GCP, or Azure, including use of Gen AI tools (e.g., GPT, LLaMA, Huggingface).
Bachelor’s or Master’s degree in Business Analytics, Computer Science, Statistics, or Data Science.
Work Experience Required: Not explicitly mentioned in the JD.
Capable of independently making informed decisions and proposing strategic, long-term improvements in AI/ML solutions and reporting.
Demonstrated ability to design and implement advanced generative AI architectures (e.g., GANs, VAEs, transformers) and evaluate using specialized metrics.
Experienced working with cross-disciplinary teams to operationalize AI solutions that address complex business challenges in a corporate technology environment.