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HomeCompaniesSmarshResearch Engineer III

Research Engineer III

Smarsh · US - Remote · Remote · Active · $25–$25 / hour · Lever

Job facts

FieldValue
CompanySmarsh
TitleResearch Engineer III
Normalized title-
Department / teamDivisions / Applied Machine Learning
LocationUnited States
Work modelRemote / Remote
Employment typeIntern Paid
Salary$25–$25 / hour
Statusactive
ATS providerLever
Posted / first seen2026-05-05 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Smarsh.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Lever.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Divisions.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanySmarsh
Sourcebe79830a-4786-443b-a6ed-7e1747ff2151
ATS providerLever

Description

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. 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. 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

Full job record

Job IDf55d4367cae488bc4ffd89ffe695555b67d166a6
Org IDc32a9bfa-7f5b-44a6-a3ad-a627b9468a95
Source IDbe79830a-4786-443b-a6ed-7e1747ff2151
Board IDbe79830a-4786-443b-a6ed-7e1747ff2151
Providerlever
Provider Job Keyb6ced21d-6674-413a-9e03-5c7348f78396
TitleResearch Engineer III
Normalized Title
Statusactive
Activeyes
Location TextUS - Remote
DepartmentDivisions
TeamApplied Machine Learning
Employment TypeIntern - Paid
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
City
Salary RawUSD 25-25 per-hour-wage
Salary Min25
Salary Max25
Salary CurrencyUSD
Salary Periodhour
Source URLhttps://jobs.lever.co/smarsh/b6ced21d-6674-413a-9e03-5c7348f78396
Apply URLhttps://jobs.lever.co/smarsh/b6ced21d-6674-413a-9e03-5c7348f78396/apply
First Seen At2026-05-29 07:06:32Z
Last Seen At2026-06-06 07:57:09Z
Last Checked At2026-06-06 07:57:09Z
Last Changed At2026-05-29 07:06:32Z
Inactive At
Source Posted At2026-05-05 15:30:01Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=lever/board=smarsh/date=2026-06-06/2026-06-06T07-57-09-006Z-fcabd344ec043033b1bf35a7a440a9f20c4a689b0520807f71afd247c2056017.json
Event Fields
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  "source_hash": "2d2090b549d74c91c446638496c40e85c134ccb3ccad837de3d92541e2ba376d",
  "last_changed_at": "2026-05-29T07:06:32.354Z",
  "active_status": "active"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "US - Remote",
    "city": null,
    "region": null,
    "country": "United States",
    "is_remote": true,
    "confidence": 0.95
  },
  "salary_max": 25,
  "salary_min": 25,
  "inferred_at": "2026-06-06T07:57:09.680Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "US - Remote",
      "city": null,
      "region": null,
      "country": "United States",
      "is_remote": true,
      "confidence": 0.95
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": "remote",
  "salary_period": "hour",
  "workplace_type": "remote",
  "salary_currency": "USD"
}
Extensions
{}
Native Structured
{
  "lists": [
    {
      "text": "How will you contribute? ",
      "content": "\n<li>Build and maintain Apache Airflow DAGs for ML pipeline orchestration&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>Develop SageMaker training jobs for NLP models (NeMo, PyTorch)</li>\n<li>&nbsp;Implement MLflow tracking and model registry integrations&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>&nbsp;Write infrastructure-as-code using Terraform (AWS S3, IAM, VPC)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>&nbsp;Create comprehensive tests for ML pipeline components&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>Follow spec-driven development practices with Claude Code&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>&nbsp;Contribute to ML observability and evaluation frameworks&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n"
    },
    {
      "text": "What will you bring?",
      "content": "\n<li>Experience with PyTorch, transformers, or other ML libraries&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>Familiarity with ML model evaluation and experimentation&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>&nbsp;Interest in ML/AI infrastructure and operations</li>\n<li>&nbsp;Strong problem-solving and debugging skills&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>Comfortable with Linux/command-line environments&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>Knowledge of AWS services (S3, SageMaker, IAM)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>Exposure to Apache Airflow or workflow orchestration&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li>\n<li>Understanding of CI/CD, testing, or infrastructure-as-code&nbsp;&nbsp;</li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1777995001792,
  "updatedAt": null,
  "categories": {
    "team": "Applied Machine Learning",
    "location": "US - Remote",
    "commitment": "Intern - Paid",
    "department": "Divisions",
    "allLocations": [
      "US - Remote"
    ]
  },
  "salaryRange": {
    "max": 25,
    "min": 25,
    "currency": "USD",
    "interval": "per-hour-wage"
  },
  "workplaceType": "remote"
}
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