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Generalist junior ML role attracts moderate applicant interest despite lesser-known employer.
Core ML and engineering skills are broadly transferable across industries with low domain lock-in.
Technical skills and tooling expectations are listed but no explicit years, creating moderate filtering.
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Own end-to-end AI/ML solutions including data cleaning, model development, deployment, and monitoring.
Develop, maintain, and integrate scalable machine learning models and AI modules into business systems under guidance.
Support data pipeline preparation, documentation, unit testing, and collaborate across teams following Agile/DevOps workflows.
Bachelor’s degree in Computer Science, Data Science, IT, or related field (Master’s preferred for senior levels).
Proficiency in Python programming and familiarity with AI/ML frameworks like TensorFlow and scikit-learn.
Knowledge of supervised and unsupervised machine learning techniques and experience with cloud ML services (AWS Sagemaker, GCP Vertex AI, Azure ML).
Work Experience Required: Not explicitly mentioned in the JD.
Comfortable operating within Agile/DevOps environments supporting AI model lifecycle from training to deployment.
Experience or interest in production-grade ML solutions involving CI/CD, model monitoring, and cloud-native tools.
Ability to translate business challenges into technical AI/ML solutions and communicate effectively with diverse stakeholders.