Mid Level AI/ML Engineer

3 days ago

Apply Now

Receive Emails with Similar Jobs

Xenon Seven

WebsiteLinkedInAll Job Openings

Artificial Intelligence • Enterprise

Xenon Seven is a company that specializes in providing AI and data solutions across various industries, including healthcare, financial services, consumer retail, high-tech, automotive, and energy utilities. With expertise in generative AI, decision support systems, predictive analytics, computer vision, robotics, and mechatronics, they support businesses in AI preparedness, exploration, transformation, and scalability. Xenon Seven works with a network of AI technologists and experts from over 20 institutions, focusing on solving complex problems and ensuring secure and seamless AI transitions for businesses. Their services aim to optimize AI infrastructure and performance while maintaining strict security standards.

11 - 50 employees

🤖 Artificial Intelligence

🏢 Enterprise

📋 Description

• Execute and deliver enterprise agentic AI solutions under guidance of senior engineers • Contribute to solution building, model development, and integration • Support Agile practices: sprint planning, estimation, and documentation • Collaborate with cross-functional teams (data scientists, DevOps, product owners) • Implement APIs, cloud-native deployments, and monitoring solutions • Focus on execution, optimization, and delivery rather than consulting

🎯 Requirements

• AI/ML Engineer (Mid-level, 4–6 years) • **Experience Level:** Mid-level, 4–6 years • **Core Skills ** • - Programming: Python, SQL, Pandas • - ML/DL frameworks: scikit-learn, PyTorch, TensorFlow • - MLOps: Docker, CI/CD • - Cloud: AWS/Azure • - AI application essentials: RAG pipelines, embeddings/vector databases, NLP/Transformers • - Agile/SCRUM practices, communication, and estimation • **Responsibilities:** • - Execute and deliver **enterprise agentic AI solutions** under guidance of senior engineers • - Contribute to **solution building, model development, and integration** • - Support **Agile practices**: sprint planning, estimation, and documentation • - Collaborate with cross-functional teams (data scientists, DevOps, product owners) • - Implement **APIs, cloud-native deployments, and monitoring solutions** • - Focus on **execution, optimization, and delivery** rather than consulting • ** More **execution-focused**, supporting senior engineers in delivery. • Expected to contribute actively to solution building, Agile practices, and enterprise agentic AI execution.