Machine Learning Framework Engineer

September 20

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Smarsh

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Smarsh enables organizations to manage the risk and uncover the value within their communications data.

cloud-based solutions • data-leak prevention • risk-based surveillance • information governance solutions • digital communications compliance

1001 - 5000

💰 Private Equity Round on 2016-01

Description

•Contribute to and oversee internal machine learning libraries to ensure scalability and efficiency across the team. •Collaborate with Data Scientists and Research Engineers to evaluate, select, and integrate machine learning tools and frameworks. •Manage and optimize AWS infrastructure to support scalable, high-performance machine learning applications. •Ability to work across datasets in text, audio, images and multilingual. •Enable highly parallelized experiments to scale efficiently across CPU and GPU resources. •Design and build end-to-end pipelines for model training, evaluation, hyperparameter optimization, bias detection, and report generation. •Maintain dataset management tools to power our data strategy. •Incorporate and manage experiment tracking systems to support research and development. •Ensure model building processes are enterprise-grade and repeatable. •Work closely with production engineering teams on end-to-end MLOps and to establish effective contracts and connection points. •Integrate and coordinate various components to build a cohesive, efficient machine learning infrastructure.

Requirements

•Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or a related field. •Extensive experience in building and managing machine learning infrastructure and tooling. •Deep knowledge of MLOps best practices, including model deployment, monitoring, and scaling. •Strong proficiency in AWS, with a proven track record of managing and optimizing cloud-based machine learning environments. Important services include EC2, Sagemaker, Batch and other ML-relevant services. •Expertise in software engineering, including Python and other programming languages commonly used in machine learning. •Excellent understanding of machine learning frameworks such as PyTorch, and Scikit-Learn, CUDA, Triton and TensorFlow. •Experience with data management and pipeline orchestration tools (e.g., Airflow, Kubeflow). •Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment. •Exceptional communication skills with a demonstrated ability to work effectively in a team-oriented environment.

Benefits

•Healthcare insurance — We provide medical, dental, and vision insurance, and a flexible spending account that allows you to set aside pre-tax dollars to pay for eligible out-of-pocket expenses. •Personal time off — A healthy work-life balance is critical to your success at the office. Smarsh offers a “take-what-you-need” time off policy, as well as flexible work arrangements. •401K Match - Smarsh provides a 4% 401K match, for which employees are fully vested on day one. •Sabbatical – The Smarsh sabbatical program provides a time to recharge, to study or simply a time to do something you are passionate about away from the workplace. Employees are eligible after six years of service. •Recognition - We’re big on kudos for a job well done. Our employee-recognition program enables co-workers to nominate their peers who best embody our core values for recognition.