Senior Machine Learning Engineer - Machine Learning Infrastructure
FlipFull Time
Senior (5 to 8 years)
Candidates are required to have at least 7 years of experience in engineering and/or data science roles, with at least 1 year in a senior role. A strong academic background (M.S. or PhD in a technical field) can substitute for some industry experience. Extensive experience developing system architecture and solving engineering problems in a major programming language like Python, Java, or C++ is necessary. A comprehensive MLOps background and experience integrating applications with cloud technologies such as AWS are essential. Expertise in MLOps frameworks like MLflow and Kubeflow, and Python-based frameworks such as PyTorch, TensorFlow, and scikit-learn are desirable. Strong communication and presentation skills, with the ability to explain complex technical topics to non-technical audiences, are also required.
The Sr. Machine Learning Engineer will lead complex ML engineering projects, design, develop, document, test, and debug software engineering solutions, and deploy, scale, and maintain machine learning models in production environments. They will develop scalable ML architecture and pipelines, collaborate with data scientists to optimize models, and identify and evaluate new platforms and technologies. Responsibilities also include defining and enforcing development best practices, mentoring junior team members, collaborating with management on roadmaps, and sharing technical knowledge and MLOps framework expertise. The role involves serving as a technical expert on ML model deployment and benchmarking, acquiring domain expertise in cybersecurity, and writing technical documentation.
Cybersecurity solutions for businesses and enterprises
Fortra provides cybersecurity solutions aimed at protecting businesses from evolving cyber threats. Their products include threat detection and response, data protection, network security, and automation tools, all designed to work together seamlessly. Fortra differentiates itself from competitors by focusing on customer success and offering integrated and scalable solutions that can adapt to the needs of both small and large organizations. The company's goal is to simplify cybersecurity for its clients, ensuring they can operate securely and efficiently in a complex digital landscape.