Smarsh
1001 - 5000 employees
Founded 2001
💸 Finance
🏢 Enterprise
☁️ SaaS
💰 Private Equity Round on 2016-01
Finance • Enterprise • SaaS
Smarsh is the global leader in communications data and intelligence, focusing on digital communications compliance and risk management in regulated industries. With over two decades of experience, Smarsh delivers AI-enabled solutions to unlock business insights from communications data at scale. Trusted by 95% of top financial firms and managing billions of messages monthly, Smarsh offers services like chat capture, email archiving, and digital risk surveillance. Their platforms are designed to meet the diverse and evolving needs of financial services, government, healthcare, and other industries, enhancing productivity and ensuring compliance with digital communication governance challenges.
Research Engineer III
🕒 May 5
🇺🇸 United States – Remote
💵 $25 / hour
👨🎓 Internship
🟡 Mid-level
🟠 Senior
📚 Research Engineer
🦅 H1B Visa Sponsor
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Smarsh
1001 - 5000 employees
Founded 2001
💸 Finance
🏢 Enterprise
☁️ SaaS
💰 Private Equity Round on 2016-01
Finance • Enterprise • SaaS
Smarsh is the global leader in communications data and intelligence, focusing on digital communications compliance and risk management in regulated industries. With over two decades of experience, Smarsh delivers AI-enabled solutions to unlock business insights from communications data at scale. Trusted by 95% of top financial firms and managing billions of messages monthly, Smarsh offers services like chat capture, email archiving, and digital risk surveillance. Their platforms are designed to meet the diverse and evolving needs of financial services, government, healthcare, and other industries, enhancing productivity and ensuring compliance with digital communication governance challenges.
📋 Description
• Build and maintain Apache Airflow DAGs for ML pipeline orchestration • Develop SageMaker training jobs for NLP models (NeMo, PyTorch) • Implement MLflow tracking and model registry integrations • Write infrastructure-as-code using Terraform (AWS S3, IAM, VPC) • Create comprehensive tests for ML pipeline components • Follow spec-driven development practices with Claude Code • Contribute to ML observability and evaluation frameworks
🎯 Requirements
• Experience with PyTorch, transformers, or other ML libraries • Familiarity with ML model evaluation and experimentation • Interest in ML/AI infrastructure and operations • Strong problem-solving and debugging skills • Comfortable with Linux/command-line environments • Knowledge of AWS services (S3, SageMaker, IAM) • Exposure to Apache Airflow or workflow orchestration • Understanding of CI/CD, testing, or infrastructure-as-code
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