Senior ML Platform Engineer [28417]

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

Job Overview

The Senior ML Platform Engineer at Stealth will play a pivotal role in the design, development, and optimization of machine learning platforms. This position requires a deep understanding of machine learning workflows and infrastructure, as well as the ability to collaborate closely with data scientists and software engineers. The successful candidate will be responsible for creating scalable and efficient machine learning solutions, enhancing the overall performance of data-driven applications, and contributing to the strategic vision of the ML engineering team.

Job Responsibilities

• Design and develop robust machine learning infrastructure to support scalable model training and deployment.
• Collaborate with cross-functional teams to implement end-to-end machine learning pipelines.
• Optimize existing algorithms and frameworks to improve performance, reliability, and efficiency.
• Conduct performance monitoring and troubleshooting of deployed models to ensure high availability.
• Stay abreast of advancements in ML technology and tools, and propose improvements to current practices.
• Provide mentorship and technical guidance to junior team members and peer engineers.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• 5+ years of experience in machine learning, software engineering, or a similar domain.
• Strong programming skills in languages such as Python, Java, or Scala.
• Proficient with ML frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with cloud platforms (AWS, Google Cloud, or Azure) and containerization technologies (Docker, Kubernetes).
• Solid understanding of data structures, algorithms, and system design principles.

Technologies & Tools

The Senior ML Platform Engineer will primarily work with state-of-the-art machine learning frameworks such as TensorFlow and PyTorch. Other tools and technologies include cloud platforms like AWS or Google Cloud for deploying and managing ML applications, container orchestration tools like Kubernetes for seamless application deployment, and programming languages including Python and Java for developing scalable machine learning solutions.

Ideal Candidates

Ideal candidates for this role will possess a strong analytical mindset coupled with exceptional problem-solving abilities. They should thrive in a fast-paced environment, showcasing an eagerness to learn and adapt to new technologies. Effective communication skills are essential for collaboration with team members and stakeholders. Additionally, a proactive attitude toward driving innovation and a passion for advancing machine learning practices are vital to ensure success in this position.