Senior/Lead Machine Learning Engineer
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Role details
Tech stack
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Job description
Experteer Overview As an ML engineer at IFS, you design and maintain scalable AI/ML infrastructure and pipelines.You collaborate with data scientists, data engineers, and DevOps to deploy production-grade AI solutions.You translate innovative AI opportunities into sustainable products while ensuring observability and drift detection.This role combines software engineering, DevOps, and ML, offering impact at scale within a global, inclusive, and innovation-driven context.Compensaciones / Beneficios - Design and maintain high-performance AI/ML infrastructure - Build and run scalable ML pipelines and model serving at scale - Develop tools for monitoring, observability, and continuous improvement - Collaborate with data scientists, data engineers, architects, and DevOps to deploy AI-driven solutions - Expand knowledge of AI infrastructure and domain processes to guide othersResponsabilidades - Proficient in Python with NumPy, Pandas, and Kserve; additional languages like Go, C#, or SQL are a plus - Familiarity with Azure cloud, infrastructure as code (Terraform, Helm), CI/CD, GitOps with ArgoCD, and containerization (Docker, Kubernetes) - Foundational ML concepts across supervised/unsupervised learning, deep learning, model evaluation - Data handling skills including preprocessing and feature engineering; experience with relational and vector databases - Strong analytical abilities to interpret complex data and derive insights - Excellent communication skills for cross-functional collaboration - Bachelor’s or Master’s in Computer Science, Software Engineering, Data Science, or related field with 3+ years in software development including AI/ML frameworks (TensorFlow, PyTorch, scikit-learn)Requisitos principales - hybrid work opportunities - inclusive workplace experiences - flexible work arrangements - opportunity to work on impactful AI solutions - global team collaboration
Requirements
This role combines software engineering, DevOps, and ML, offering impact at scale within a global, inclusive, and innovation-driven context.Compensaciones / Beneficios - Design and maintain high-performance AI/ML infrastructure - Build and run scalable ML pipelines and model serving at scale - Develop tools for monitoring, observability, and continuous improvement - Collaborate with data scientists, data engineers, architects, and DevOps to deploy AI-driven solutions - Expand knowledge of AI infrastructure and domain processes to guide othersResponsabilidades - Proficient in Python with NumPy, Pandas, and Kserve; additional languages like Go, C#, or SQL are a plus - Familiarity with Azure cloud, infrastructure as code (Terraform, Helm), CI/CD, GitOps with ArgoCD, and containerization (Docker, Kubernetes) - Foundational ML concepts across supervised/unsupervised learning, deep learning, model evaluation - Data handling skills including preprocessing and feature engineering; experience with relational and vector databases - Strong analytical abilities to interpret complex data and derive insights - Excellent communication skills for cross-functional collaboration - Bachelor’s or Master’s in Computer Science, Software Engineering, Data Science, or related field with 3+ years in software development including AI/ML frameworks (TensorFlow, PyTorch, scikit-learn)Requisitos principales - hybrid work opportunities - inclusive workplace experiences - flexible work arrangements - opportunity to work on impactful AI solutions - global team collaboration
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