Principal Machine Learning Engineer - MLOps

Porto, Porto District, Portugal

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI & Machine Learning, AI, Data EngineeringIndustries

Requirements

The ideal candidate will have over 8 years of relevant experience in Machine Learning, Data Engineering, or MLOps roles, with a proven track record of building, deploying, and maintaining ML systems in production. Proficiency in ML frameworks like PyTorch, TensorFlow, and Scikit-learn is essential, as is hands-on experience with MLflow, SageMaker, and Azure ML for model training, tracking, and deployment. Skills in CI/CD pipelines for ML using GitHub Actions, Azure DevOps, and Terraform, along with expertise in model observability, monitoring, and drift detection, are required. Experience building and managing ML pipelines using Airflow and Azure Data Factory, coupled with cloud infrastructure expertise in Azure (primary) and AWS (secondary), is necessary. Familiarity with containerization and orchestration using Docker and Kubernetes (AKS) is also expected.

Responsibilities

This Principal Machine Learning Engineer will focus on ML Ops and ML Platform development, supporting scalable AI systems across Digital and Retail use cases. The role involves building, deploying, and maintaining ML systems in production environments, utilizing ML frameworks and MLOps tools. Responsibilities include implementing CI/CD pipelines for ML, ensuring model observability and monitoring, and managing ML pipelines. The engineer will leverage cloud infrastructure, primarily Azure, and containerization technologies like Docker and Kubernetes.

Skills

MLOps

ML Platform development

PyTorch

TensorFlow

Scikit-learn

MLflow

SageMaker

Azure ML

CI/CD

GitHub Actions

Azure DevOps

Terraform

Model observability

Model monitoring

Drift detection

Airflow

Azure Data Factory

Azure

AWS

Docker

Kubernetes

AKS

Mineral

Develops AI tools for sustainable agriculture

About Mineral

Mineral.ai develops technology solutions aimed at improving the agriculture industry. The company utilizes perception technology, artificial intelligence (AI), and machine learning (ML) to create tools that help farmers, researchers, and agricultural advisors increase crop yields, manage pests, and adapt to climate change. Their products include precision agriculture tools that optimize resource use and advanced data analytics platforms that provide insights from agricultural data. Unlike many competitors, Mineral.ai focuses on creating partnerships within the agriculture sector to co-develop solutions, enhancing their product offerings. The goal of Mineral.ai is to support sustainable food production and help feed the world more efficiently.

Mountain View, CaliforniaHeadquarters

N/AYear Founded

VENTURE_UNKNOWNCompany Stage

Food & Agriculture, AI & Machine LearningIndustries

51-200Employees

Risks

Transition from Alphabet may lead to financial instability and resource loss.

Licensing model could reduce control over technology application and revenue stability.

Difficulty in monetizing technology indicates challenges in creating durable revenue streams.

Differentiation

Mineral.ai uses AI and ML to revolutionize agriculture with precision tools.

The company partners with industry leaders like Driscoll's for real-world technology applications.

Mineral.ai's licensing model allows broad integration into existing agribusiness systems.

Upsides

Licensing model increases market reach and technology integration in agribusiness.

Partnerships with companies like Driscoll's enhance technology application and sustainability goals.

Growing interest in agrivoltaic systems offers new partnership opportunities for Mineral.ai.

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