Senior Platform ML Engineer [28817]

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Job Overview

The Senior Platform ML Engineer at Stealth will be responsible for designing, building, and deploying scalable machine learning models and platforms. This role requires a deep understanding of machine learning algorithms, as well as a strong software engineering background. The engineer will collaborate with cross-functional teams to integrate ML solutions into our product offerings and ensure high availability and performance. The ideal candidate will leverage their expertise to drive innovation and improve the efficiency of our data-driven initiatives.

Job Responsibilities

• Design, implement, and optimize machine learning algorithms for various applications.
• Build and maintain scalable ML platforms that support the deployment of models.
• Collaborate with data scientists and product teams to define project scopes and requirements.
• Conduct experiments to evaluate the effectiveness of ML models and propose improvements.
• Ensure the reliability and performance of machine learning applications through rigorous testing and monitoring.
• Document processes and provide training to internal stakeholders regarding ML best practices.
• Stay abreast of industry trends and emerging technologies in machine learning and AI.

Qualifications

• Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or related field.
• 5+ years of experience in machine learning engineering or a related field.
• Proficiency in programming languages such as Python, Java, or C++.
• Experience with ML frameworks and libraries such as TensorFlow, PyTorch, or Scikit-Learn.
• Strong knowledge of software engineering principles and best practices.
• Familiarity with cloud platforms (AWS, Google Cloud Platform, Azure) and containerization technologies (Docker, Kubernetes).
• Excellent problem-solving skills and ability to work in a fast-paced environment.

Technologies & Tools

This position utilizes a range of technologies and tools, including but not limited to: Apache Spark for big data processing, TensorFlow and PyTorch for building machine learning models, Docker for containerization, and AWS for cloud infrastructure. Familiarity with version control systems such as Git is also essential for collaborative development work. The role requires a strong toolkit to manage data, run experiments, and deploy solutions effectively.

Ideal Candidates

The ideal candidate for the Senior Platform ML Engineer position is a proactive and innovative problem-solver with a passion for technology and data. They possess strong analytical skills and an ability to communicate complex concepts in a clear manner. Candidates should thrive in collaborative environments, be adaptable to changing requirements, and demonstrate leadership qualities in driving projects to successful completion. A keen interest in continuous improvement and learning is highly valued, as is the ability to mentor junior team members.