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Metro location, generic Software Engineer title, 3+ years requirement, and broad full-stack+ML skills increase applicant density.
ML production and MLOps focus requires domain-specific experience but full-stack skills remain transferable across industries.
Explicit 3+ years and mandatory production ML experience plus MLOps and multiple tech requirements raise filtering strictness.
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Develop and maintain full-stack software and ML-driven applications using Java, Spring Boot, Python, and ReactJS.
Build and deploy machine learning models and data pipelines, including feature engineering and model evaluation processes.
Collaborate with cross-functional teams to translate business requirements into scalable ML-integrated technical solutions and participate in code reviews and root cause analysis.
Bachelor’s degree in Computer Science, Data Science, or a related field (or equivalent experience).
Minimum 3 years of software development experience with strong exposure to ML implementation and building/deploying ML models in production.
Proficient in Java/Spring Boot, ReactJS, Python with ML frameworks (scikit-learn, TensorFlow, PyTorch).
Experience with PostgreSQL or similar databases and familiarity with Agile/Scrum and SDLC practices.
Experienced in end-to-end ML pipeline development including data ingestion, model training, deployment, and monitoring.
Comfortable working in enterprise environments with complex, scalable software and ML systems involving microservices and CI/CD pipelines.
Able to integrate ML workflows with application development and collaborate effectively with product and data teams.