Factored via Greenhouse

Senior MLOps Engineer

LATAM senior

still open verified 1d ago posted 585d ago seen 3h ago

Posted 585 days ago, which is unusual. The employer's own board was still carrying it when we last read it, 3 hours ago.

Apply at job-boards.greenhouse.io

This is the employer's own posting, not a copy on a job board.

What we know

Is it still open?

Confirmed still open

Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.

We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.

Check this listing's status as JSON

How old is it?

Posted 585d ago

The date the source published, not the day we noticed it (2025-03-26). Last seen at its source 3h ago.

We have tracked this listing since 3 Sep 2026 (60 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.

Is it remote?

The listing says yes

The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.

Who may apply?

LATAM

The description states no restriction of its own. This is the source's own tag.

Pay not stated

Similar roles pay $6,000–7,250/mo

Middle 50% of 39 listings that do state pay — Engineering · Senior · LATAM · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.

Skills named in the ad

AWSAzureBashCI/CDDockerGCPGitHub ActionsGitLab CIGrafanaInfrastructure as CodeJenkinsKubernetesMLOpsMLflowMachine LearningMicroservicesPrometheusPythonScriptingTerraform

Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.

Carried by 1 source

Greenhouse employer's own board first seen 60d ago · last seen 3h ago

The listing

Fully remote | Complete engagement job

Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.

At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.

As an MLOps Engineer, you will design, build, and maintain the infrastructure, pipelines, and tools that enable seamless machine learning deployment and operation across enterprise environments. You’ll bridge the gap between Machine Learning and Software Engineering, owning ML workflows end-to-end from automated training and versioning to production monitoring and continuous integration.

Functional Responsibilities:

Build and automate continuous integration and deployment (CI/CD) pipelines tailored for machine learning models and data workflows using tools like GitHub Actions, GitLab CI, or Jenkins.
Architect and manage containerized microservices and orchestration platforms for ML workloads using Docker and Kubernetes (EKS, GKE, AKS).
Implement and manage ML lifecycle, tracking, and versioning tools such as MLflow, DVC, or Kubeflow.
Provision, configure, and maintain ML cloud infrastructure using Infrastructure as Code (IaC) tools like Terraform.
Establish comprehensive monitoring, alerting, and logging systems for deployed models using tools like Prometheus, Grafana, or Arize to track data drift, model performance, and operational health.
Collaborate with data scientists and software engineers to transition ML models from experimental scripts into secure, low-latency, and scalable production APIs.

Qualifications:

5+ years of hands-on experience in MLOps, with a proven track record of deploying and scaling ML pipelines in enterprise environments.
Advanced English proficiency (written and spoken) with strong communication skills to collaborate effectively across multidisciplinary teams.
Strong Python and Bash scripting skills, with expertise in containerization (Docker) and orchestration frameworks (Kubernetes).
Deep hands-on experience with cloud platforms (AWS, GCP, Azure), Infrastructure as Code (Terraform), and CI/CD pipelines.
Demonstrated experience with dedicated MLOps platforms (MLflow, DVC, Kubeflow) and model observability/monitoring solutions (Prometheus, Grafana, Arize).

Our Benefits:

Ownership through equity participation.
Annual company retreat.
Education bonus for continuous learning.
Company-wide winter break.
Paid time off.
Optional in-person events and meetups.
Tailored career roadmaps.
High-performance culture.

At Factored, we believe that passionate, smart people expect honesty and transparency, as well as the freedom to do the best work of their lives while learning and growing as much as possible. Great people enjoy working with other passionate, smart people, so we believe in hiring right, and are very selective about who joins our team. Once we hire you, we will invest in you and support your career and professional growth in many meaningful ways. We hire people who are supremely intelligent and talented, but we recognize that intelligence is not enough. Perhaps more importantly, we look for those who are also passionate about our mission and are honest, diligent, collaborative, kind to others, and fun to be around. Life is too short to work with people who don’t inspire you.

We are a transparent workplace, where EVERYBODY has a voice in building OUR company, and where learning and growth are available to everyone based on their merits, not just on stamps on their resume. As impressive as some of the stamps on our resumes are, we recognize that human talent and passion exist everywhere, and come from many backgrounds, so stamps matter much less than results. All of us are dedicated doers and are highly energetic, focusing vehemently on execution because we know that the best learning happens by doing. We recognize that we are creating OUR COMPANY TOGETHER, which is not only a high-performing fast-growing business but is changing the way the world perceives the quality of technical talent in Latin America. We are fueled by the great positive impact we are making in the places where we do business and are committed to accelerating careers and investing in hundreds (and hopefully thousands) of highly talented data science engineers and data analysts.

In short, our business is about people, so we hire the best people and invest as much as possible in making them fall in love with their work, their learning, and their mission. When not nerding out on data science, we love to make music together, play sports, play games, dance salsa, cook delicious food, brew the best coffee, throw the best parties, and generally have a great time with each other.