IUNU
Machine Learning Engineer
11 days ago
About the Job
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.
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
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; a Master’s degree is a plus
Benefits:
- Comprehensive benefits, including healthcare and generous paid leave
- Opportunities for career growth within a fast-growing and innovative company
- Competitive Paid Time Off (PTO) policy
About the Company

IUNU
<p class="break-words white-space-pre-wrap t-black--light text-body-medium">Founded in 2013, IUNU (“you knew”) is building the future of the controlled environment agriculture (CEA) industry. The company's AI-driven LUNA platform enables growers to develop a feedback loop between capturing data and managing processes to create precise, predictable production.</p>
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