Machine Learning Engineer

• Must have strong hands-on experience in Python programming, API development, and cloud-native application development (4 Years Minimum).
• Must have experience building prototypes, solution accelerators, and enterprise integrations using cloud technologies.
• Must have two years’ experience with Google Cloud Platform (GCP), Vertex AI, Gemini APIs, or similar AI platforms.
• Must have experience in Prompt Engineering, LLM application development, and AI solution implementation.
• Must have experience developing Agentic AI workflows, AI agents, and orchestration frameworks.
• Must have experience with REST APIs, microservices, and third-party system integrations.
• Must have experience working with containerization, CI/CD, and production deployment practices.

Must possess strong stakeholder communication and customer-facing solutioning skills

Preferred Skills

Google Professional ML Engineer certification is preferred.

Applied analytics experience and the ability to convert prototype outcomes into clear value narratives are preferred.

• Design and develop AI-powered prototypes, accelerators, and customer-facing solutions.
• Build and integrate applications using Gemini APIs, Vertex AI, and Google Cloud services.
• Develop agentic workflows, AI assistants, and multimodal solution demonstrations.
• Collaborate with customers, partners, and cross-functional teams to validate business use cases.
• Translate business requirements into scalable technical architectures and solutions.
• Build Proof of Concepts (PoCs) and demonstrate business value through rapid prototyping.
• Support deployment, optimization, and troubleshooting of AI solutions in cloud environments.

Stay current with emerging AI technologies and apply them to customer scenarios