Senior Platform ML Engineer [28837]

This job was posted over 30 days ago, so it has most likely closed. See newer jobs like it.

Written by AI from the job title and company, not by Stealth, so some details may not match this job. The employer's own page has the real description.

Job Overview

The Senior Platform ML Engineer at Stealth will play a pivotal role in architecting and implementing machine learning frameworks that drive the deployment and optimization of high-impact ML models. This individual will collaborate closely with cross-functional teams to develop state-of-the-art solutions that meet business objectives. The ideal candidate will be responsible for enhancing performance, scalability, and reliability of machine learning algorithms within the platform, ensuring robust data pipelines, and facilitating the integration of ML processes across various systems.

Job Responsibilities

• Design, develop, and maintain scalable machine learning systems and applications.
• Collaborate with data scientists and software engineers to refine model architectures and algorithms for production readiness.
• Optimize ML models for performance and scalability across various cloud environments.
• Implement and monitor best practices for data preprocessing, feature engineering, and model evaluation.
• Lead the integration of ML tools and libraries into existing infrastructure.
• Conduct code and algorithm reviews, providing constructive feedback to team members.
• Engage in continuous learning and adaptation of new technologies within the ML landscape.

Qualifications

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, or related field.
• Minimum of 5 years of experience in machine learning engineering or a similar role.
• Proficient in programming languages such as Python, Java, or C++.
• Deep understanding of machine learning algorithms, data structures, and statistical methods.
• Experience with cloud services (AWS, Google Cloud, Azure) and scalable ML solutions.
• Solid experience in deploying machine learning models into production.
• Strong familiarity with frameworks such as TensorFlow, PyTorch, or similar.

Technologies & Tools

The Senior Platform ML Engineer will primarily work with Python, TensorFlow, and PyTorch for model development and tuning. Cloud computing platforms such as AWS, Azure, or Google Cloud will be essential for deploying scalable ML solutions. Familiarity with tools for data management, such as Apache Kafka or Apache Spark, is also beneficial, alongside version control systems such as Git and CI/CD pipelines for efficient development processes.

Ideal Candidates

The ideal candidate for the Senior Platform ML Engineer role will possess strong analytical thinking, creativity, and problem-solving skills. They will demonstrate effective communication abilities to collaborate closely with diverse teams, spanning from data scientists to stakeholders. A proactive approach to learning new technologies and methodologies and a passion for driving innovation within the machine learning field is essential. Candidates should be adaptable and capable of thriving in a fast-paced, evolving environment.