Machine Learning Engineer
Cloudflare
MLOps
BHOUT
full-time
Posted on:
Location Type: Hybrid
Location: Lisbon • 🇵🇹 Portugal
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AndroidAWSAzureCloudDockerJavaJenkinsKotlinPythonPyTorchTensorflow
About the role
- Design and maintain end-to-end ML pipelines for data ingestion, model training, validation, and deployment.
- Build CI/CD workflows for model deployment.
- Implement model versioning, tracking, and experiment management using tools such as MLflow or Weights & Biases.
- Collaborate in ML, CV, and NLP projects to streamline the transition from research to production.
- Establish best practices for reproducibility, security, and management of ML systems.
- Integrate edge AI frameworks (TFLite, ONNX Runtime) to deploy models directly on BHOUT’s devices.
- Support continuous learning pipelines, enabling models to adapt with new data from live training sessions.
Requirements
- 5+ years of experience in Machine Learning Infrastructure, MLOps, or Applied ML Engineering.
- Proven experience building automated ML pipelines for training and deployment.
- Strong proficiency in Python and experience with frameworks such as PyTorch, TensorFlow.
- Hands-on knowledge of MLflow, Weights & Biases, Jenkins, or Docker for model management and orchestration.
- Familiarity with cloud platforms (e.g., AWS, Azure).
- Experience with edge AI optimization (quantization, pruning, model distillation).
- Solid understanding of DevOps principles and CI/CD for ML systems.
- Familiarity with Android development (Kotlin/Java) and NDK for native integrations.
- Strong debugging, automation, and scripting skills.
- Excellent collaboration and communication skills with AI teams.
Benefits
- Play BHOUT: Enjoy free BHOUT Club membership.
- Competitive Compensation: Competitive salary and performance-based bonuses.
- Extra Time Off: Enjoy 25 vacation days per year, plus 3 additional days off on your birthday, Christmas Eve, and New Year’s Eve.
- Work-Life Balance: Work on your terms with BHOUT's flexible hours and hybrid/remote work options!
- Entrepreneurial Environment: Dynamic atmosphere where every voice is heard, and every idea has the potential to make a significant impact.
- Team Get-Togethers: Regular team events and off-sites to foster collaboration and camaraderie!
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Machine Learning InfrastructureMLOpsApplied ML Engineeringautomated ML pipelinesPythonPyTorchTensorFlowedge AI optimizationDevOps principlesCI/CD
Soft skills
collaborationcommunicationdebuggingautomationscripting