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 designing and implementing advanced machine learning platforms that drive the organization’s data-driven initiatives. This position requires a combination of software engineering skills, machine learning expertise, and a strong understanding of cloud-based architectures. The successful candidate will be responsible for developing scalable ML solutions, optimizing existing models, and ensuring platform reliability while collaborating closely with cross-functional teams to accelerate the deployment of machine learning applications.

Job Responsibilities

• Design, develop, and maintain machine learning platforms and infrastructure.
• Implement scalable and robust ML workflows for data preprocessing, model training, and deployment.
• Collaborate with data scientists and product teams to translate machine learning algorithms into production-ready code.
• Ensure the reliability and efficiency of machine learning models through rigorous testing and optimization.
• Monitor system performance and troubleshoot any issues that arise, maintaining high levels of operational readiness.
• Stay up-to-date with industry trends and emerging technologies, identifying opportunities for platform enhancements.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a related field; Master's degree preferred.
• Minimum of 5 years of experience in software development with a focus on machine learning.
• Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow or PyTorch.
• Experience with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).
• Solid understanding of MLOps concepts and best practices.
• Proficient with version control systems such as Git and CI/CD pipelines.

Technologies & Tools

The Senior ML Platform Engineer will utilize a variety of technologies and tools to accomplish their tasks effectively. Commonly used technologies include Python for developing machine learning models, TensorFlow and PyTorch for constructing and training ML frameworks, and cloud-based platforms such as AWS and Google Cloud for deployment. Additionally, the role involves leveraging Docker for containerization and Kubernetes for orchestration of ML workloads.

Ideal Candidates

Ideal candidates for this position will possess a strong analytical mindset, coupled with the ability to solve complex problems. They should demonstrate exceptional skills in software development and be passionate about machine learning and AI technologies. Moreover, successful candidates will exhibit excellent communication skills to effectively collaborate with diverse teams and stakeholders, along with a continuous learning attitude to adapt to the ever-evolving tech landscape.