Smarsh

Research Engineer III

Reposted 5 Hours Ago

Hiring Remotely in US

Remote

Mid level

Software

The Role

The Research Engineer III will build and maintain ML infrastructure, develop NLP models, implement tracking integrations, and ensure observability in ML pipelines.

Summary Generated by Built In

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.

Skills Required

Experience with PyTorch, transformers, or other ML libraries
Familiarity with ML model evaluation and experimentation
Knowledge of AWS services (S3, SageMaker, IAM)
Exposure to Apache Airflow or workflow orchestration
Understanding of CI/CD, testing, or infrastructure-as-code

Smarsh Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Smarsh and has not been reviewed or approved by Smarsh.

Leave & Time Off Breadth — Time off is characterized by unlimited PTO, generous vacation allowances, and paid holidays, with policies that support taking time away. These elements are positioned as a core strength that helps balance lower base pay in some roles.
Wellbeing & Lifestyle Benefits — Perks include wellness programs, commuter and bike reimbursement, volunteer time off, peer recognition, remote-work support, and a sabbatical option. The variety of non-salary benefits contributes to a supportive work-life environment.
Retirement Support — A 401(k) with employer match and profit sharing is offered, with immediate vesting described for the match. This strengthens the long-term financial component of total rewards.