ML Platform Engineer, Contractor

🔥 0 minutes ago

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

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

Upload Resume

myPOS

WebsiteLinkedInAll Job Openings

201 - 500 employees

Dive into a new world of payments with myPOS to find out how the latest payment technologies will grow your business.

📋 Description

• Build and maintain MLOps automation end-to-end: CI/CD for models and pipelines, environment management, artifact versioning (models, data, prompts, code), and release governance • Implement and operate model serving infrastructure: deployment patterns (blue/green, canary, shadow), endpoint management, scaling, and latency/throughput optimisation • Build and maintain training and experimentation infrastructure: job orchestration, compute provisioning, experiment tracking, hyperparameter management, and reproducibility tooling • Implement observability for ML systems: data quality checks, feature drift detection, model performance monitoring, bias checks, alerting, and incident response workflows • Build and maintain data pipelines for ingestion, transformation, feature engineering, and export across multiple sources and destinations • Design and maintain a feature store or feature platform layer: serving consistency, point-in-time correctness, and reuse across teams • Expose well-governed datasets, features, and APIs that models, pipelines, and downstream consumers can rely on • Enforce secure data handling and compliance with relevant data protection standards, access controls, and audit requirements • Contribute to documentation, platform standards, and continuous improvement of ML engineering processes across teams

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience) • 5+ years of Data or ML Engineering experience, with at least 3 years shipping ML systems to production. • Strong Python skills (typed code, async, testing) and solid SQL fluency. • Hands-on MLOps experience: model registries, experiment tracking (MLflow or Vertex Experiments), pipeline orchestration, and reproducible training runs. • Strong DevOps fundamentals: CI/CD (GitHub Actions, Cloud Build, or similar), IaC (Terraform), containerization (Docker). • Familiarity with at least one major cloud provider (GCP, AWS, Azure) and deploying data solutions in the cloud • Experience building and maintaining data pipelines with orchestrators (Airflow/Composer, Dagster) and distributed engines (Spark, BigQuery) • Strong troubleshooting mindset: ability to debug issues across data, infra, pipelines, and deployments • Collaborative mindset and clear communication across engineering, analytics, and business stakeholders

🏖️ Benefits

• Annual salary reviews, promotions and performance bonuses • myPOS Academy for upskilling and training • Unlimited access to courses on LinkedIn Learning • Annual individual training and development budget • Refer a friend bonus as we know that working with friends is fun • Teambuilding, social activities and networks on a multi-national level