Platform Engineer – MLOps

🕒 September 22

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 40%

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.

Apply Now

Find Similar Remote Jobs

Opplane

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

🤖 Artificial Intelligence

💳 Fintech

☁️ SaaS

🔥 Funding within the last year

💰 Accelerator/Incubator on 2025-12

Artificial Intelligence • Fintech • SaaS

Opplane is a software company that helps organizations unlock the value of data through connectivity, data governance, and generative AI. It focuses on applying AI-driven data solutions to regulated environments, especially banking and fintech, enabling compliance, secure data connectivity, and AI use cases for financial services and enterprises.

📋 Description

• Build and maintain CI/CD pipelines for ML workloads, including testing, packaging, and promotion of models and pipelines • Own ML lifecycle tooling for experiment tracking, model registry, versioning, and promotion gates • Define development-to-production promotion procedures, including validation gates, rollback, and audit trails • Implement model deployment and serving patterns for batch inference and real-time endpoints • Build and maintain observability for ML workloads, covering pipeline health, model and data drift, performance, latency, and cost • Partner with data scientists to productionize notebooks and experiments into governed, reliable, repeatable pipelines • Administer and evolve Databricks workspaces, Unity Catalog metastores, and catalogs with appropriate access controls • Support AWS infrastructure underpinning the Lakehouse, particularly IAM, networking, S3, and related platform services • Apply least-privilege access and Unity Catalog governance across data and ML assets • Monitor and tune Databricks jobs and compute for cost and performance • Maintain architecture documentation and runbooks for deployment, troubleshooting, and production support • Partner with data engineering and data science teams to define and maintain platform standards, automation, and documentation • Translate ML workload requirements into reliable, governed, reusable platform capabilities

🎯 Requirements

• 5+ years of relevant experience in platform, DevOps, MLOps, ML engineering, or related engineering roles • Hands-on experience with the ML lifecycle: experiment tracking, model registry, versioning, and deployment (MLflow or equivalent) • Experience building CI/CD pipelines using Git-based workflows for ML or data workloads • Working experience with Databricks platform capabilities, including workspaces, Unity Catalog, compute, jobs/workflows, permissions, and environment configuration • Solid Python scripting for automation and pipeline tooling • Ability to work closely with data scientists and data engineers to translate ML requirements into reliable platform capabilities • Fluency in English (written and spoken) • AWS experience, particularly IAM, networking, S3, and related platform services (nice to have) • Infrastructure as Code experience with Terraform or Terragrunt (nice to have) • Familiarity with Databricks Asset Bundles, Delta Live Tables, or Databricks Workflows (nice to have) • Exposure to feature stores or feature platforms such as Chalk, or real-time model serving (nice to have) • Experience with notebook-based data science environments such as Domino Data Lab (nice to have) • Experience with on-premises or hybrid Kubernetes environments and Git-based deployment workflows using GitLab (nice to have) • Databricks ML Associate or AWS certifications (nice to have) • Observability tooling such as CloudWatch and Prometheus/Grafana, and cost-optimization practices (nice to have)

🏖️ Benefits

• Permanent full-time employment • Remote work • Global and multicultural environment with diverse perspectives and global collaboration • Startup energy in a fast-moving, impact-driven environment • Ownership mindset where engineers own what they build • Collaborative, friendly, open, curious, and supportive culture

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume