Senior Platform ML Engineer [28837]

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Job Overview

As a Senior Platform ML Engineer at Stealth, you will play a pivotal role in designing and implementing advanced machine learning solutions that enhance our platform's capabilities. You will collaborate with cross-functional teams to develop robust algorithms, optimize performance, and ensure high-quality deployment in production environments. Your expertise will contribute to the improvement of data processing pipelines and the establishment of best practices in machine learning engineering. This position requires a blend of technical acumen, innovative problem-solving skills, and the ability to work effectively in a dynamic team atmosphere.

Job Responsibilities

• Design, develop, and deploy scalable machine learning models for various applications.
• Collaborate closely with data scientists and software engineers to integrate models into existing platforms.
• Optimize model performance and ensure code quality through best practices and automated testing.
• Lead efforts to improve data ingestion and preprocessing pipelines.
• Monitor and maintain models in production, utilizing advanced monitoring techniques.
• Document processes and models to facilitate knowledge sharing within the team.
• Stay updated with the latest developments in machine learning and contribute to strategic planning.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in machine learning engineering or a related field.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks/tools, such as TensorFlow, PyTorch, or Scikit-learn.
• Strong understanding of algorithms, data structures, and software design principles.
• Familiarity with cloud services (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
• Excellent analytical and problem-solving skills with attention to detail.

Technologies & Tools

The Senior Platform ML Engineer will work with a variety of cutting-edge technologies and tools, including but not limited to TensorFlow, PyTorch, Apache Spark for big data processing, and Docker for containerization. Familiarity with cloud platforms like AWS, Google Cloud Platform, or Azure is essential for deploying machine learning models at scale. Additionally, knowledge of SQL and NoSQL databases will be crucial for data management tasks.

Ideal Candidates

Ideal candidates for the Senior Platform ML Engineer position will possess a strong technical foundation combined with excellent communication skills. They should exhibit a passion for innovation and continuous learning, along with the ability to work collaboratively in a fast-paced environment. Successful candidates will demonstrate a proactive approach to problem-solving and the capacity to adapt to evolving project requirements while maintaining a focus on results and quality.