
Building Scalable ML Solutions
1 day ago
We are seeking a skilled Machine Learning Engineer to join our team. As a key member of our organization, you will design, build, and deploy scalable ML models that power our cutting-edge food safety platform.
Main Responsibilities:
- Design, train, and deploy machine learning models for real-world biotech applications.
- Collaborate with data scientists, engineers, and domain experts to translate requirements into production-ready ML solutions.
- Optimize model performance and ensure reliability in production environments.
- Implement pipelines for data preprocessing, feature engineering, and model monitoring.
- Work closely with backend teams to integrate ML models into applications and APIs.
Required Skills and Qualifications:
- 2–5 years of experience as an ML Engineer or in a similar role.
- Strong proficiency in Python, machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience deploying models at scale (cloud platforms: AWS/GCP/Azure).
- Knowledge of MLOps tools (Docker, Kubernetes, CI/CD for ML pipelines).
- Solid understanding of data structures, algorithms, and software engineering best practices.
Perks:
- 100% remote work option.
- Opportunity to apply ML in high-impact biotech solutions.
- Startup culture: autonomy, innovation, and ownership.
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