Senior ML Platform Engineer [28417]

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Position Overview

The Senior ML Platform Engineer at Stealth will play a pivotal role in advancing our machine learning infrastructure and capabilities. This position involves the design, development, and maintenance of robust ML platforms that ensure high performance, scalability, and security. The candidate will collaborate closely with data scientists and software engineers to optimize the deployment of machine learning models and frameworks, enabling impactful data-driven solutions for the organization.

Job Responsibilities

• Design and implement scalable, reliable ML systems and services to support data science initiatives.
• Collaborate with cross-functional teams to understand requirements and provide tailored solutions to meet ML needs.
• Develop and maintain tools for efficient model versioning, monitoring, and performance metrics.
• Evaluate and integrate emerging technologies to enhance the ML platform capabilities.
• Conduct performance tuning and optimization of machine learning models in production.
• Ensure compliance with data governance and security best practices throughout the ML lifecycle.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum of 5 years of experience in machine learning engineering or related roles.
• Strong proficiency in programming languages such as Python, Java, or Scala.
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
• Familiarity with cloud platforms (AWS, Google Cloud, Azure) and their ML services.
• Expertise in software development methodologies and tools (Git, CI/CD, Agile).
• Proven experience with distributed systems and massive data processing frameworks (Hadoop, Spark).

Technologies & Tools

The Senior ML Platform Engineer will engage with a variety of technologies and tools essential for machine learning and data processing. Key technologies include cloud-based environments such as AWS or GCP, containerization tools like Docker and Kubernetes, as well as orchestration frameworks for machine learning pipelines, such as Apache Airflow. Experience with SQL and NoSQL databases will also be integral for data management, in addition to being proficient in version control and CI/CD tools.

Ideal Candidates

Ideal candidates for this position will possess a forward-thinking mindset and a strong passion for leveraging technology to solve complex problems. They should exhibit excellent problem-solving abilities, a collaborative spirit, and a keen attention to detail. The ability to thrive in a fast-paced environment while managing multiple projects simultaneously will be crucial. Furthermore, candidates should be enthusiastic about continuous learning and adapting to new tools and methodologies in the ever-evolving field of machine learning.