Company Description Job Spread is focused on connecting organizations with candidates who have the skills needed to succeed in specific roles. The company helps businesses fill vacancies efficiently by matching job requirements with qualified talent. By understanding both employer needs and candidate capabilities, Job Spread aims to create meaningful, long-term employment relationships. Team members contribute to building data-driven solutions that improve hiring outcomes and support growth for clients and professionals alike.
Role Description The Machine Learning Engineer will design, implement, and deploy machine learning models that improve Job Spread’s ability to match candidates with open roles. Responsibilities include collecting and preprocessing data, developing and evaluating algorithms, and optimizing models for performance and scalability. The engineer will collaborate with product, engineering, and data teams to integrate ML solutions into production systems and monitor their effectiveness. This is a full-time, on-site role based in the San Francisco Bay Area, requiring regular in-person collaboration and participation in cross-functional projects.
Qualifications
Strong foundation in Computer Science and Algorithms, including data structures and algorithmic problem-solving.
Experience with Pattern Recognition and Neural Networks for building and improving predictive models.
Solid understanding of Statistics for model evaluation, experimentation, and data analysis.
Proficiency in one or more programming languages commonly used in ML (such as Python), and familiarity with ML frameworks (such as TensorFlow or PyTorch).
Experience working with large datasets, data pipelines, and version control tools.
Ability to translate business requirements into technical solutions and communicate findings clearly to non-technical stakeholders.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
Experience deploying machine learning models in production environments and monitoring their performance is highly beneficial.

Machine Learning Engineer

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