Software Engineer, Machine Learning Infrastructure

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Written by AI from the job title and company, not by Stripe, so some details may not match this job. The employer's own page has the real description.

Job Overview

As a Software Engineer specializing in Machine Learning Infrastructure at Stripe, you will be responsible for designing, developing, and maintaining scalable machine learning systems that empower the company's payment solutions. You will collaborate with data scientists and product teams to build robust infrastructure capable of efficiently handling large datasets and facilitating advanced analytics. This role requires a strong foundation in software engineering principles, a deep understanding of machine learning frameworks, and a commitment to delivering high-quality, performant solutions.

Job Responsibilities

• Design and implement scalable machine learning infrastructure solutions to support various business applications.
• Collaborate with data scientists and engineers to optimize existing ML models and workflows.
• Develop and maintain robust APIs to enable seamless integration of ML models into Stripe's services.
• Monitor, test, and troubleshoot machine learning systems to ensure high reliability and performance.
• Research and incorporate cutting-edge technologies and methodologies into the ML infrastructure.
• Provide documentation and training on machine learning tools and best practices to cross-functional teams.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering with a focus on machine learning or data processing.
• Proficient in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks like TensorFlow, PyTorch, or similar.
• Strong understanding of cloud computing platforms (e.g., AWS, GCP, Azure) and their ML services.
• Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
• Excellent problem-solving skills and ability to work collaboratively in a fast-paced environment.

Technologies & Tools

In this role, you will be working with various technologies and tools that enhance the ML infrastructure, including cloud platforms (AWS, GCP), machine learning libraries (TensorFlow, PyTorch), big data frameworks (Spark, Hadoop), and container management tools (Docker, Kubernetes). Familiarity with CI/CD pipelines and version control systems (Git) is also essential for effective collaboration and deployment.

Ideal Candidates

Ideal candidates for the Software Engineer, Machine Learning Infrastructure position at Stripe will possess a thorough understanding of both software development and machine learning concepts. They will demonstrate strong analytical and problem-solving skills, coupled with a proactive and collaborative approach to work. A willingness to stay abreast of the latest technologies and a drive for continuous improvement will further enhance their suitability for this dynamic role within a leading financial technology company.