Mineral

ML Engineer

Blumenau, State of Santa Catarina, Brazil

Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
GamingIndustries

Requirements

Candidates should possess 3-5 years of experience as an ML Engineer, preferably with a background in the Gaming industry, and demonstrate experience with ML frameworks such as TensorFlow, Scikit-Learn, and PyTorch. They should also have a strong background in MLOps practices, including CI/CD, containerization (Docker), orchestration frameworks (Kubernetes, Airflow), model serving tools (AWS SageMaker, Databricks MLFlow), model observability frameworks, automation, and feature stores.

Responsibilities

The ML Engineer will develop large-scale distributed machine learning systems, collaborate with cross-functional teams to deploy and integrate machine learning models, liaise with business units to address their ML needs and contribute to the cross-BU ML portfolio, optimize feature extraction, transformation, and selection, work with and manage feature stores for reusability, ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform, and contribute to evaluating and adopting new technologies and tools to enhance machine learning capabilities.

Skills

TensorFlow
Scikit-Learn
Pytorch
ML Frameworks
Distributed Machine Learning
Model Training
Model Versioning
Model Monitoring
MLOps
CI/CD
Docker
Kubernetes
Airflow
AWS SageMaker
Databricks MLFlow
Model Observability
Feature Stores
Automation

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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