Senior MLOps Engineer

Job not on LinkedIn

🔥 3 minutes ago

💃 Latin America – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Factor Funding Company

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1 - 10 employees

Founded 1996

📦 Logistics

🏭 Manufacturing

💼 Consulting

Logistics • Manufacturing • Consulting

Factor Funding Company is a financial services provider specializing in small business funding through various options such as accounts receivable factoring, asset-based loans, and purchase order financing. By converting invoices and receivables into immediate cash, they help businesses quickly improve cash flow without the lengthy processes associated with traditional lending. Their services cater to the needs of small businesses across multiple industries, allowing them to focus on growth and operations while alleviating cash flow concerns.

📋 Description

• Build and automate CI/CD pipelines for machine learning models and data workflows using 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 tools like Terraform. • Establish monitoring, alerting, and logging systems for deployed models using 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, scalable production APIs. • Design, build, and maintain infrastructure, pipelines, and tools enabling seamless machine learning deployment and operation across enterprise environments. • Own ML workflows end-to-end, from automated training and versioning to production monitoring and continuous integration.

🎯 Requirements

• 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).

🏖️ 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.

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