Senior ML Platform Engineer

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Job Overview

The Senior ML Platform Engineer at Barrington James will be responsible for designing, implementing, and maintaining advanced machine learning platforms that support cutting-edge algorithms and data-driven applications. This role combines aspects of software development, systems architecture, and machine learning workflow orchestration, facilitating the seamless integration of machine learning solutions into production environments. The ideal candidate will collaborate closely with data scientists and engineering teams, ensuring optimal performance of model deployment and operational excellence across the platform.

Job Responsibilities

• Design and architect scalable ML platform solutions that can handle large volumes of data and complex workloads.
• Implement machine learning models in production, optimizing deployment and monitoring for continuous performance improvement.
• Collaborate with data scientists to enhance model development workflows and streamline model testing and validation processes.
• Develop and maintain automated data pipelines to facilitate data ingestion for machine learning applications.
• Monitor and troubleshoot performance issues within the ML platform, ensuring high availability and reliability.
• Provide technical mentorship to junior engineers and team members, promoting knowledge sharing and best practices.
• Stay abreast of the latest trends and advancements in machine learning and relevant technologies.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related discipline.
• At least 5 years of experience in software engineering or machine learning platforms.
• Proven experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong proficiency in programming languages such as Python, Java, or Scala.
• Experience with cloud services and platforms (e.g., AWS, Google Cloud Platform, Azure).
• Solid understanding of data structures, algorithms, and software design principles.
• Familiarity with DevOps practices, CI/CD pipelines, and version control systems like Git.

Technologies & Tools

The Senior ML Platform Engineer will work with a diverse set of technologies and tools, including cloud computing platforms like AWS and GCP for scalable infrastructure, machine learning frameworks such as TensorFlow and PyTorch for model development, and tools like Apache Kafka and Apache Airflow for data pipeline management. Additionally, familiarity with containerization technologies like Docker and orchestration platforms such as Kubernetes will be essential to ensure seamless deployment and management of machine learning services.

Ideal Candidates

Ideal candidates for the Senior ML Platform Engineer position exhibit strong analytical skills, an innate curiosity about machine learning technologies, and a passion for continuous learning. They are expected to have excellent problem-solving abilities, strong communication skills for effective collaboration with cross-functional teams, and a proactive approach to tackling challenges in the machine learning deployment space. A successful candidate will also have a commitment to quality and performance in their work, demonstrating leadership in driving projects toward successful outcomes.