Senior ML Platform Engineer [28417]

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Overview

The Senior ML Platform Engineer at Stealth will play a critical role in enhancing and optimizing the machine learning infrastructure and workflows. This position involves collaborating with cross-functional teams to build scalable and efficient platforms for developing, deploying, and monitoring machine learning models. The ideal candidate will leverage their expertise in both software engineering and machine learning to drive innovation and ensure the seamless integration of machine learning solutions within various products and services.

Job Responsibilities

• Develop and maintain scalable machine learning pipelines to support model training, validation, and deployment.
• Collaborate closely with data scientists to optimize algorithms and enhance model performance.
• Design and implement tools for monitoring machine learning models in production.
• Ensure the reliability and efficiency of machine learning systems through automation and robust testing procedures.
• Stay abreast of the latest advancements in machine learning technology and methodologies.
• Conduct code reviews and mentor junior engineers, fostering a culture of knowledge-sharing.
• Participate in architectural discussions to shape the evolution of the machine learning infrastructure.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field; Master’s degree preferred.
• 5+ years of experience in software engineering, with a focus on machine learning and data analytics.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of data structures and algorithms along with experience in software design principles.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Proven track record of delivering complex projects on time and within scope.

Technologies & Tools

In this role, candidates will utilize a variety of technologies and tools, including but not limited to Python, TensorFlow, and PyTorch for developing machine learning models, as well as Docker and Kubernetes for containerization and orchestration. Familiarity with cloud-based services from AWS, Google Cloud, or Azure is essential for deploying and managing applications. Techniques for Continuous Integration and Continuous Deployment (CI/CD) will also be employed to enhance the efficiency of the development process.

Ideal Candidates

The ideal candidates for the Senior ML Platform Engineer position will possess a strong analytical mindset and a passion for problem-solving. They should be self-motivated, detail-oriented, and capable of working both independently and in team settings. A commitment to continuous learning and the ability to adapt to new technologies will be crucial for success. Furthermore, excellent communication skills are essential, as collaboration with technical and non-technical teams will be a significant aspect of this role.