Machine Learning Engineer

-Purpose of the Job:

Eruvaka Technologies serves the aquaculture industry by designing and building advanced feeding systems that utilize complex algorithms, IoT and machine learning to precisely feed the shrimp. These systems help farmers to improve the profitability, protect the pond eco-systems by reducing the feed usage and provides the farmers with valuable insights. With customers in over 8 countries, we are expanding rapidly to deploy our systems across the world to achieve our mission of sustainable aquaculture.

You will be part of the team that builds our appetite based intelligent feeding system for shrimp. This system uses underwater passive acoustic sensors to estimate shrimp appetite and dispenses feed accordingly.

Responsibilities:

1. Model Development:
• Design, train, and optimize machine learning models to interpret underwater acoustic signals for shrimp feeding patterns.
• Implement real-time prediction systems to guide feeding schedule

2. Data Analysis & Preprocessing:

• Collect, clean, and preprocess underwater acoustic data.
• Analyze signal pattern to extract features relevant to shrimp appetite and activity.

3. System Integration:

• Collaborate with IoT teams to integrate machine learning solutions into edge devices and cloud systems.
• Ensure system scalability, robustness, and accuracy in real-world farming environments.

4 Research & Optimization:

• Stay updated with the latest advancements in machine learning and signal processing.
• Conduct experiments to improve model performance and adapt to environmental variability.

Preferred candidate profile

• Strong knowledge of machine learning algorithms and frameworks (TensorFlow, PyTorch, Scikit-learn).
• Proficiency in programming languages like Python (mandatory) and familiarity with Java (preferred).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn) and statistical analysis.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and deploying machine learning models on edge devices.
• Strong problem-solving skills, attention to detail, and the ability to work with noisy and unstructured data.

Experience:

• 3-5 years of experience in machine learning and data analysis
• Exposure to IoT systems and real-time processing is a plus.