Overview
ML Engineer Jobs in Doha, Qatar at malomatia
Title: ML Engineer
Company: malomatia
Location: Doha, Qatar
Job Description
Must Have
- 4+ years of software or machine-learning engineering experience, including hands-on experience deploying models to production.
- Demonstrated track record operationalizing models developed by data scientists into reliable, scalable, and observable production systems.
- Production experience with classical machine-learning workloads — distinct from generative-AI application development.
- Strong collaboration skills across data science, software engineering, and platform teams.
- Commitment to building reliable, well-engineered, and maintainable systems.
Nice to Have
- Experience with feature stores and large-scale or streaming data pipelines.
- Knowledge of infrastructure-as-code (e.g., Terraform) and cloud cost optimization.
- Experience with workflow orchestration tools (e.g., Apache Airflow).
- Familiarity with model-serving frameworks and API design for inference.
- Light exposure to generative-AI or LLM deployment.
- Experience operating systems in a regulated or enterprise environment.
- Cloud or MLOps certifications.
Responsibilities
- Build, deploy, and maintain production machine-learning pipelines, from data ingestion and feature processing through to model serving.
- Operationalize models developed by data scientists, ensuring reliability, scalability, reproducibility, and performance.
- Implement MLOps practices including CI/CD for machine learning, model versioning, automated retraining, and model registries.
- Design and maintain feature pipelines and, where relevant, feature stores.
- Set up monitoring and alerting for model performance, data drift, and system health, and respond to degradation.
- Optimize inference latency, throughput, and resource cost for deployed models.
- Containerize and orchestrate machine-learning workloads using Docker and Kubernetes on Oracle Cloud Infrastructure (OCI).
- Automate and harden data and model workflows to reduce manual intervention.
- Collaborate with data scientists on model handoff, packaging, and success metrics.
- Work with software engineers to integrate models into client-facing applications and services.
- Apply software-engineering best practices including testing, code review, and documentation to machine-learning systems.
- Troubleshoot and resolve production issues across the model-serving stack.
Qualifications
- Bachelor's degree in Computer Science, Software Engineering, or a related field; equivalent experience accepted.
- Strong Python engineering skills and production experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
- Hands-on experience with MLOps tooling (e.g., MLflow, Kubeflow) and CI/CD pipelines.
- Proficiency with containerization and orchestration (Docker, Kubernetes).
- Experience building and maintaining data pipelines and processing large datasets.
- Experience with cloud infrastructure, ideally Oracle Cloud Infrastructure (OCI) and OCI Data Science.
- Understanding of model monitoring, drift detection, and retraining strategies.
- Solid software-engineering fundamentals including testing and version control.
