EarnIn
Staff Machine Learning Engineer (Applied ML)Mountain View, US
EarnIn, Mountain View, California, United States, 94043
Staff Machine Learning Engineer (Applied ML)
Machine learning is the crucial enabler for every financial service that EarnIn provides to its community members. We are going through transformative investments in machine learning platforms and algorithms. We seek experienced ML engineers to shape and execute our vision of bringing state-of-the-art capabilities to our machine learning stack. The Mountain View base salary range for this full-time position is $272,700 to $333,300, plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Mountain View, requiring in-office work 2 days a week. What You'll Do
Design, build, and maintain the ML platform and tools to support the end-to-end machine learning lifecycle. Work closely with other machine learning engineers to understand their workflows, optimize model training and deployment processes, and ensure the reproducibility of results. Ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform. Contribute to the evaluation and adoption of new technologies and tools to enhance our machine-learning capabilities. Provide technical guidance and mentorship to junior team members. Set examples of outstanding operational excellence. Be the catalyst of step-jump changes. What We're Looking For
Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 7+ years of industry machine learning experience and excellent software engineering skills. Strong programming skills in Python, with familiarity with machine learning (ML) frameworks such as TensorFlow or PyTorch. Experience with ML cloud platforms such as AWS Sagemaker, Databricks, or GCP Vertex AI. Familiarity with data pipelines and workflow management tools. Strong communication and collaboration skills. Passion for learning and staying updated with the latest industry trends in machine learning and platform engineering. At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant. EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.
Machine learning is the crucial enabler for every financial service that EarnIn provides to its community members. We are going through transformative investments in machine learning platforms and algorithms. We seek experienced ML engineers to shape and execute our vision of bringing state-of-the-art capabilities to our machine learning stack. The Mountain View base salary range for this full-time position is $272,700 to $333,300, plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Mountain View, requiring in-office work 2 days a week. What You'll Do
Design, build, and maintain the ML platform and tools to support the end-to-end machine learning lifecycle. Work closely with other machine learning engineers to understand their workflows, optimize model training and deployment processes, and ensure the reproducibility of results. Ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform. Contribute to the evaluation and adoption of new technologies and tools to enhance our machine-learning capabilities. Provide technical guidance and mentorship to junior team members. Set examples of outstanding operational excellence. Be the catalyst of step-jump changes. What We're Looking For
Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 7+ years of industry machine learning experience and excellent software engineering skills. Strong programming skills in Python, with familiarity with machine learning (ML) frameworks such as TensorFlow or PyTorch. Experience with ML cloud platforms such as AWS Sagemaker, Databricks, or GCP Vertex AI. Familiarity with data pipelines and workflow management tools. Strong communication and collaboration skills. Passion for learning and staying updated with the latest industry trends in machine learning and platform engineering. At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant. EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.