Senior Platform Engineer, Machine Learning
Fieldguide188,000 - 213,500 USD/year
- Full Time
- Senior (5 to 8 years), Mid-level (3 to 4 years)
Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
GamingIndustries
Requirements
The ideal candidate should possess 3-5 years of experience as an ML Engineer, preferably with a background in the Gaming industry, and demonstrate proficiency in ML frameworks such as TensorFlow, Scikit-Learn, and PyTorch. They should have experience with model training, versioning, and monitoring, along with a strong understanding of 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
This role involves developing large-scale distributed machine learning systems that are scalable, performant, efficient, and reliable, collaborating with cross-functional teams to help deploy and integrate machine learning models, liaising with business units to address their ML needs and contribute to the cross-BU ML portfolio, optimizing feature extraction, transformation, and selection, working with and managing feature stores for reusability across ML pipelines, ensuring scalability, reliability, cost efficiency, and ease of use of the machine learning platform, and contributing to the evaluation and adoption of new technologies and tools to enhance machine learning capabilities.
Skills
TensorFlow
Scikit-Learn
Pytorch
ML Frameworks
Model Training
Model Versioning
Model Monitoring
MLOps
CI/CD
Docker
Kubernetes
Airflow
AWS SageMaker
Databricks MLFlow
Feature Stores
Model Deployment
Distributed Machine Learning
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.
Key Metrics
Mountain View, CaliforniaHeadquarters
N/AYear Founded
VENTURE_UNKNOWNCompany Stage
Food & Agriculture, AI & Machine LearningIndustries
51-200Employees