Senior ML Platform Engineer [28417]

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Job Overview

The Senior Machine Learning Platform Engineer at Stealth will play a crucial role in developing and maintaining a robust platform for machine learning operations. This position involves collaborating closely with cross-functional teams to design, build, and enhance machine learning workflows and infrastructure. The ideal candidate will leverage their expertise to optimize existing processes, ensure scalability, and implement best practices in ML model deployment and monitoring. Their contributions will empower data scientists and machine learning engineers to deliver impactful insights and solutions effectively and efficiently.

Job Responsibilities

• Design and implement scalable architecture for machine learning models and applications.
• Develop and maintain ML workflows, ensuring high availability and performance.
• Integrate various data sources into the ML platform for enhanced analysis and model training.
• Monitor and troubleshoot ML systems to ensure optimal performance and reliability.
• Collaborate with data scientists and software engineers to facilitate seamless model deployment.
• Advocate for best practices in ML and data management across teams.
• Conduct code reviews and provide mentorship to junior engineers.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in machine learning, software development, or a related area.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with ML frameworks and libraries like TensorFlow, PyTorch, or Scikit-Learn.
• Demonstrated expertise in cloud computing platforms (e.g., AWS, Azure, GCP).
• Solid understanding of data engineering principles and practices.
• Strong problem-solving skills and the ability to work in a fast-paced environment.

Technologies & Tools

The Senior ML Platform Engineer will work with a variety of modern technologies and tools, including but not limited to cloud-based platforms like Amazon Web Services (AWS) or Google Cloud Platform (GCP), machine learning frameworks like TensorFlow and PyTorch, and CI/CD tools for automating deployment processes. Additionally, familiarity with containerization technologies such as Docker and Kubernetes will be essential for managing scalability and performance of machine learning applications.

Ideal Candidates

Ideal candidates for the Senior ML Platform Engineer position will possess a combination of technical acumen and collaborative spirit. They should demonstrate a passion for machine learning and a desire to solve complex problems through innovative solutions. The ability to communicate effectively with both technical and non-technical stakeholders is crucial, along with a proactive approach to identifying challenges and driving projects to completion. Candidates who value mentorship and knowledge sharing will thrive in the environment Stealth fosters.