The Research Engineer III will build and maintain ML infrastructure, develop NLP models, implement tracking integrations, and ensure observability in ML pipelines.
Who are we?
Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.
Join our team building production ML infrastructure for enterprise-scale machine learning pipelines.You'll work on a platform that orchestrates end-to-end ML workflows from data ingestion through model training, evaluation, and deployment.
How will you contribute?
- 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
What will you bring?
- 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
About our culture
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
