Senior ML Platform Engineer [28417]

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.

Overview

The Senior ML Platform Engineer at Stealth will play a pivotal role in designing, building, and maintaining scalable machine learning platforms that support the development and deployment of state-of-the-art ML models. This position demands a profound understanding of machine learning frameworks and cloud infrastructure, where the engineer will collaborate with data scientists and software engineers to ensure seamless integration and functionality of ML systems. The ideal candidate will exhibit strong problem-solving skills, leadership capabilities, and a strategic mindset to drive innovative solutions and improve existing processes.

Job Responsibilities

• Design and implement scalable ML platforms and infrastructure to support modeling and data processing needs.
• Collaborate with cross-functional teams to enhance model performance and optimize resource utilization.
• Develop automated pipelines for training, testing, and deploying machine learning models.
• Maintain and improve existing ML systems, ensuring high availability and performance.
• Integrate and manage big data tools and frameworks to process large datasets efficiently.
• Conduct research on emerging technologies and recommend solutions that enhance the company's ML capabilities.
• Mentor and guide junior engineers, providing technical leadership and support.

Qualifications

• Bachelor's or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
• 5+ years of experience in software engineering with a focus on machine learning and data science.
• Strong proficiency in programming languages such as Python, Java, or Scala.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
• Proficient in cloud technologies, particularly AWS, Azure, or GCP.
• Hands-on experience with containerization tools like Docker and orchestration tools like Kubernetes.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.

Technologies & Tools

The Senior ML Platform Engineer will primarily work with a comprehensive suite of technologies and tools that include Python, TensorFlow, PyTorch, AWS services (such as S3, EC2, Lambda), Docker, Kubernetes, and various big data technologies like Apache Spark and Hadoop. Familiarity with CI/CD tools and monitoring solutions is also essential to ensure the integrity and robustness of ML deployments.

Ideal Candidates

The ideal candidates for the Senior ML Platform Engineer role possess a strong analytical mindset and a passion for leveraging machine learning to solve complex problems. They should exhibit excellent communication skills, allowing them to articulate technical concepts to non-technical stakeholders effectively. Furthermore, a successful candidate will demonstrate adaptability and a proactive approach to continuous learning and improvement, thriving in a dynamic and innovative work environment.