Senior Machine Learning Platform Engineer, ML Foundations

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Overview

The Senior Machine Learning Platform Engineer in ML Foundations at Block will play a crucial role in enhancing the machine learning capabilities of the organization. This position involves architecting, designing, and developing robust machine learning platforms that facilitate the deployment, scalability, and performance of machine learning models. The engineer will work closely with cross-functional teams including data scientists, software engineers, and product managers to ensure optimal integration and utilization of machine learning technologies, driving innovation and efficiency across the organization.

Job Responsibilities

• Design and implement scalable machine learning platforms and tools.
• Collaborate with data scientists to create reusable model training and deployment solutions.
• Optimize model performance and ensure system reliability in production environments.
• Develop and maintain CI/CD pipelines for machine learning workflows.
• Identify and implement best practices for machine learning processes and data handling.
• Conduct performance tuning of machine learning algorithms and systems.
• Provide technical guidance and mentorship to junior engineers and data scientists.

Qualifications

• Master’s or Ph.D. degree in Computer Science, Statistics, Mathematics, or related field.
• 5+ years of experience in machine learning, data engineering, or a related discipline.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
• Solid understanding of machine learning algorithms, data structures, and models.
• Hands-on experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Strong knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Excellent problem-solving skills and a collaborative mindset.

Technologies & Tools

The Senior Machine Learning Platform Engineer will utilize a variety of technologies and tools to build and maintain machine learning infrastructure. Key tools include cloud services (AWS, Google Cloud), machine learning libraries and frameworks (TensorFlow, PyTorch), container orchestration tools (Docker, Kubernetes), and CI/CD frameworks (Jenkins, GitLab). Proficiency in data management platforms and version control systems will also be crucial to support efficient model development and deployment processes.

Ideal Candidates

The ideal candidate for the Senior Machine Learning Platform Engineer position will possess a strong blend of technical acumen and collaborative spirit. They will demonstrate a desire to innovate and streamline processes, showing an enthusiasm for problem-solving and a proactive approach to challenges. The perfect fit will also exhibit excellent communication skills, enabling them to convey complex technical concepts to non-technical stakeholders effectively. A strong focus on quality, performance, and efficiency in their work, along with a commitment to professional growth and development, will characterize the ideal candidate.