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Mid-level, popular AI role with broad ML requirements attracts many qualified applicants.
Core ML/AI modeling skills are widely transferable across industries.
Explicit 3–5 years, required production ML experience and specified libraries increases selection strictness.
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Design, train, and optimize AI/ML models using frameworks such as Kubeflow, PyTorch, TensorFlow, and HuggingFace focusing on deep learning, NLP, computer vision, and classical ML.
Translate business use cases into scalable AI architectures, including preprocessing and feature engineering, collaborating with cross-functional teams for integration and deployment readiness.
Mentor junior engineers, document model development processes, and ensure compliance with data privacy, bias mitigation, and governance standards.
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
3–5 years of experience designing and deploying AI/ML models in production environments.
Strong Python programming skills and extensive experience with ML/DL libraries (Kubeflow, PyTorch, TensorFlow, scikit-learn).
Understanding of model lifecycle management including versioning, monitoring, and deployment readiness in coordination with MLOps teams.
Experienced AI engineer with proven ability to deliver production-ready AI solutions aligned to business use cases with measurable impact.
Strong collaborator capable of working with technical and non-technical stakeholders across distributed teams (Europe, US, India).
Skilled in advanced AI domains such as transformers, embedding techniques, image recognition, reinforcement learning, and cloud-based deployments.