Applied Machine Learning Engineer

IUNU • Seattle, WA

13d

About The Position

At IUNU (“you knew’), we’re revolutionizing the agriculture industry through cutting-edge AI-driven solutions for greenhouse operations. Our mission is to empower growers with insights that drive operational efficiency, enhance crop yields, and reduce environmental impact. We are seeking an Applied Machine Learning Engineer for our AI team to developing products for our clients and the greenhouse industry. Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and programming. If you also have knowledge of data science and software engineering, we’d like to meet you. Your ultimate goal will be to shape and build efficient self-learning applications.

Requirements

• 3-5 years of proven experience as a Machine Learning Engineer or a similar role
• Strong experience with Deep Learning
• Understanding of data structures, data modeling, and software architecture
• Deep knowledge of math, probability, statistics, and algorithms
• Ability to write robust code in Python, Java, and R
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
• Excellent communication skills
• Ability to work in a team
• Outstanding analytical and problem-solving skills
• BSc in Computer Science, Mathematics, or a similar field

Nice To Haves

• a Master’s degree is a plus

Responsibilities

• Study and transform data science prototypes
• Design machine learning systems
• Research and implement appropriate ML algorithms and tools
• Develop machine learning applications according to requirements
• Select appropriate datasets and data representation methods
• Run machine learning tests and experiments
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems when necessary
• Extend existing ML libraries and frameworks
• Keep abreast of developments in the field

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 51-100 employees