
Advanced Data Scientist Role
1 day ago
We are seeking a skilled Machine Learning Engineer to design, build, and deploy scalable ML models that power our cutting-edge food safety platform.
The successful candidate will have experience designing, training, and deploying machine learning models for real-world biotech applications. They will work closely with data scientists, engineers, and domain experts to translate requirements into production-ready ML solutions.
Key Responsibilities:- Design and Deploy Scalable ML Models: Develop and implement efficient machine learning algorithms and models that can be deployed at scale in production environments.
- Collaborate with Cross-Functional Teams: Work closely with data scientists, engineers, and domain experts to translate business requirements into production-ready ML solutions.
- Optimize Model Performance: Optimize model performance and ensure reliability in production environments through continuous monitoring and improvement.
- Implement Data Pipelines: Design and implement pipelines for data preprocessing, feature engineering, and model monitoring to ensure high-quality data and accurate model performance.
- Experience: 2–5 years of experience as an ML Engineer or in a similar role.
- Skills: Strong proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and experience deploying models at scale (cloud platforms: AWS/GCP/Azure).
- Knowledge: Solid understanding of data structures, algorithms, and software engineering best practices. Experience with MLOps tools (Docker, Kubernetes, CI/CD for ML pipelines) is a plus.
- Experience with Scientific/Biotech/Healthcare Data: Experience working with scientific/biotech/healthcare data is highly desirable.
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