Senior ML Platform Engineer [28417]

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Job Overview

As a Senior ML Platform Engineer at Stealth, you will play a pivotal role in designing, developing, and maintaining our machine learning platforms. Your expertise will enable the team to deploy scalable and efficient models, enhancing our data-driven capabilities. Working closely with cross-functional teams, you will ensure that our solutions meet the highest standards of reliability and performance, ultimately contributing to the success of our innovative projects.

Job Responsibilities

• Design and implement scalable machine learning platform architectures that support various ML models and workflows.
• Collaborate with data scientists to understand model requirements and optimize performance.
• Develop and maintain deployment pipelines for continuous integration and delivery of ML applications.
• Monitor system performance and implement improvements for efficiency and scalability.
• Provide technical mentorship to junior engineers and contribute to the team's knowledge base.
• Ensure best practices in software engineering and machine learning are followed throughout the project lifecycle.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
• 5+ years of experience in software engineering or machine learning engineering roles.
• Proficiency in programming languages such as Python, Java, or Scala.
• Strong experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Deep understanding of cloud platforms (AWS, Azure, GCP) and container orchestration technologies (Docker, Kubernetes).
• Excellent problem-solving skills and a proactive approach to challenges.
• Experience with data pipeline and ETL tools.

Technologies & Tools

The Senior ML Platform Engineer role requires proficiency with a variety of technologies and tools to ensure the effective deployment and management of machine learning models. Key technologies used include cloud services such as AWS, Azure, or Google Cloud Platform for scalable infrastructure, along with deployment tools like Docker and Kubernetes for containerization. Familiarity with CI/CD tools such as Jenkins and GitLab, as well as data processing frameworks like Apache Spark will also be crucial in this role.

Ideal Candidates

The ideal candidate for the Senior ML Platform Engineer position will exhibit a strong blend of technical expertise and innovative thinking. They should be results-oriented, displaying an eagerness to tackle complex challenges and drive seamless integrations of machine learning solutions. A collaborative mindset is essential, as the candidate will work extensively with diverse teams. Furthermore, excellent communication skills will facilitate the sharing of knowledge and foster a culture of learning within the organization.