Machine Learning Engineer

Company Description

Join a multibillion-dollar global company that brings together amazing technology, people, and operational scale to become a powerhouse in the memory industry. Headquartered in Rancho Cordova, California, Solidigm combines elements of an established, successful technology company with the spirit, agility, and entrepreneurial mindset of a start-up. In addition to the U.S. headquarters and other facilities in the U.S., the company has international presence in Asia, Europe, and the Americas. Solidigm will continue to lead the world in innovating new Memory technologies with aspirations to be the #1 NAND memory company in the world. At Solidigm, we view problems as opportunities to define innovative solutions that hold the power to change the world and unleash the potential technological needs that the future holds. At Solidigm, we are One Team that fosters a diverse, equitable, and inclusive culture that embraces individual uniqueness and empowers us to bring our best selves to deliver excellence in support of Solidigm's vision and mission to be the go-to partner for optimized data storage solutions. You can be part of the takeoff of an innovative business that develops cutting-edge products, delivers strong business value for customers, provides an engaging workplace for its employees, and serves a greater impact on the world. This is a golden opportunity for the right applicant to join us and help design, build, and lead Solidigm. We want a diverse team of dedicated professionals who will not just be Solidigm team members but contribute to how we shape the future of the organization. We are seeking applicants who will grow and thrive in our culture; be customer inspired, trusting, innovative, team-oriented, inclusive, results driven, collaborative, passionate, and flexible.

Job Description

The Entry-Level Machine Learning Engineer will assist in designing, developing, and deploying machine learning models and generative AI solutions to help solve business problems. In this role, you will support data scientists by preparing data, conducting model experiments, and maintaining scalable AI environments. You'll collaborate closely with a team of experienced data scientists and engineers, gaining hands-on experience with modern machine learning frameworks, software engineering principles, and cloud infrastructure. We are looking for a candidate with a foundational knowledge of machine learning, enthusiasm for continuous learning, strong analytical thinking, and excellent collaboration skills. Key Responsibilities

• Assist in creating, training, and deploying machine learning models for various business applications.
• Support the development and maintenance of scalable and efficient environments where data scientists can experiment and refine ML models.
• Collaborate with data scientists and senior engineers to understand project requirements and support model optimization and integration.
• Help integrate machine learning models into existing systems, applications, and workflows.
• Monitor and assist in improving model accuracy, performance, and efficiency through experimentation and analysis.
• Learn and apply software engineering best practices, such as version control, testing, and documentation, to ML and Generative AI projects
• Stay current with emerging AI technologies and techniques through ongoing professional development.
• Assist in the implementation of data security and privacy standards in all AI activities.
• Support the development and maintenance of automated pipelines for data preprocessing, model training, and deployment.

Qualifications

• Bachelor’s degree (or upcoming graduation) in Computer Science, Data Science, Machine Learning, or a related technical field.
• Academic or internship experience in developing and experimenting with machine learning models.
• Proficiency with Python.
• Familiarity with common machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Exposure or coursework related to cloud platforms (e.g., AWS, Azure, Google Cloud) is a plus.
• Basic understanding of software engineering best practices, including version control (e.g., Git), unit testing, and documentation.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively in a team environment.

Additional Information

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