Contract: Machine Learning Operations Specialist

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$61,842 U.S. median for this role

Projected growth (BLS Employment Projections)

+1.9% - Slower

Matched to SOC 11-1021 - Operations aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Operations From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Contract: Machine Learning Operations Specialist Remote: Argentina; Brazil; Chile; Colombia; Costa Rica; Mexico Why You'll Love This Role: We're looking for an experienced Machine Learning Engineer to join the ML team at Newsela. This team works on projects ranging from classical Machine Learning to AI / Generative pipelines. This is a hands-on role. You'll work closely with ML/AI, data and site reliability engineers to take models from prototype to production, build robust data pipelines, and keep our services running smoothly as we continue to scale. What You'll Be Doing: - Design and maintain CI/CD pipelines for ML model training, packaging, and deployment across our microservices. - Manage containerized services on AWS ECS, optimizing for cost, latency, and availability. - Automate infrastructure provisioning and service configuration with Terraform. - Work to maintain and scale services that make use of third party LLM providers. - Build and improve data pipelines that feed models from BigQuery, S3, and DynamoDB into training and inference workflows. - Instrument services with observability tooling (Datadog, OpenTelemetry, Langfuse) and establish SLOs for model-serving endpoints. - Collaborate with ML engineers to productionize new models using BentoML, FastAPI, and container-based serving. About You: - 2-3 years in ML Ops supporting ML/AI features, systems and workflows with 3-4 years prior experience in DevOps, CloudOps or SRE. - Strong proficiency in Python. - Hands-on experience with Docker containerization and container orchestration. - Solid understanding of CI/CD for ML workflows in an enterprise production environment. - Experience with Infrastructure as Code, preferably Terraform.

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