Senior Platform ML Engineer [28417]

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Job Overview

The Senior Platform ML Engineer at Stealth will play a pivotal role in designing and implementing machine learning models to optimize our platform capabilities. This individual will collaborate closely with cross-functional teams to develop scalable solutions, enhance the overall architecture, and address complex data challenges. The ideal candidate will have extensive experience in machine learning frameworks and a deep understanding of both software development and data science principles to drive innovation and efficiency within our infrastructure.

Job Responsibilities

• Design, deploy, and maintain scalable machine learning models on the platform.
• Collaborate with data scientists and software engineers to integrate ML algorithms into production systems.
• Monitor, troubleshoot, and optimize machine learning systems for performance and reliability.
• Conduct research to identify new techniques and technologies for platform enhancement.
• Document processes and develop best practices for using machine learning within the organization.
• Provide mentorship and technical guidance to junior engineers and team members.
• Participate in code reviews to ensure high-quality standards and improve the codebase.

Qualifications

• Master’s or Ph.D. in Computer Science, Data Science, or a related field.
• A minimum of 5 years of experience in machine learning and software engineering.
• Proficient in programming languages such as Python, Java, or Scala.
• Strong hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Familiarity with cloud services (AWS, Azure, GCP) for deploying ML models.
• Solid understanding of data structures, algorithms, and software design principles.
• Proven track record in working with large datasets and data processing technologies such as Hadoop or Spark.

Technologies & Tools

The Senior Platform ML Engineer will work with various technologies and tools, including machine learning libraries such as TensorFlow and PyTorch, data processing frameworks like Apache Spark and Hadoop, and cloud platforms such as AWS and Google Cloud Platform. Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes will be advantageous for orchestrating machine learning workloads effectively.

Ideal Candidates

The ideal candidate for the Senior Platform ML Engineer position is someone who possesses a strong analytical mindset, is intrinsically motivated, and demonstrates excellent problem-solving skills. They should have a collaborative spirit, thrive in a fast-paced environment, and show a passion for exploring cutting-edge machine learning technologies. Additionally, strong communication skills and the ability to simplify complex concepts for various stakeholders are crucial for success in this role.