
Machine Learning Deployment Specialist
2 weeks ago
We are seeking an experienced MLOps professional to join our team. The ideal candidate will have a strong background in working with machine learning model deployment pipelines.
- Design, build, and manage scalable ML model deployment pipelines.
- Automate model training, validation, monitoring, and retraining workflows.
- Implement model governance, versioning, and reproducibility best practices.
- Collaborate with data scientists, engineers, and product teams to operationalize ML solutions.
- Ensure robust monitoring and performance tuning of deployed models.
The successful candidate will work closely with our data analysts, engineers, and business teams to ensure optimal performance, scalability, and availability of our data pipelines and analytics.
About Our Work Environment:
We foster a values-driven and people-centric work environment that enables our employees to accelerate growth, both professionally and personally, impact the world in powerful, positive ways, using the latest technologies, enjoy collaborative innovation, with diversity and work-life wellbeing at the core.
- We offer flexible working hours and hybrid work options to accommodate various needs and preferences.
- Our workspace is equipped with accessible facilities, including adjustable workstations, ergonomic chairs, and assistive technologies to support employees with physical disabilities.
What We Are Looking For:
- Strong experience with MLOps tools & frameworks (MLflow, Kubeflow, SageMaker, Vertex AI).
- Proficient in containerization (Docker, Kubernetes).
- Good knowledge of cloud platforms (AWS, Azure, or GCP).
- Expertise in Python and familiarity with ML libraries (TensorFlow, PyTorch, scikit-learn).
- Solid understanding of CI/CD, infrastructure as code, and automation tools.
If You Thrive in Our Culture:
We welcome applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference.
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