
Senior Machine Learning Operations Specialist
1 day ago
Job Description:
We are seeking a seasoned Machine Learning Operations Engineer to join our team. The ideal candidate will have 2+ years of experience in deploying, monitoring, and scaling ML models on cloud platforms.
Main Responsibilities:
- Model Deployment: Deploy and monitor ML models on AWS (SageMaker, EKS, Lambda) or GCP (Vertex AI, GKE, Cloud Functions)
- Pipeline Management: Build and maintain CI/CD pipelines for ML workflows using GitHub Actions / Jenkins / cloud-native tools
- Containerization: Containerize and orchestrate workloads with Docker & Kubernetes; manage infrastructure via Terraform/CloudFormation
- Observability: Implement model registries, feature stores, and observability using MLflow, Feast, Prometheus/Grafana
- Collaboration: Collaborate with data scientists to operationalize ML models for personalization, recommendations, NLP
- Technical Skills: Proficient in Python, ML frameworks (Scikit-learn, TensorFlow, PyTorch), and data pipelines (Airflow, Spark, SQL)
- Bonus Skills: Experience with real-time ML serving, A/B testing, or media/recommender systems is a bonus
Requirements:
- Experience: Experience with subscription, media, or recommender systems is a plus
- Knowledge: Knowledge of experiment design & causal inference is a plus
- Exposure: Exposure to real-time ML serving (KFServing, Seldon, Ray Serve) is a plus
Education:
A Bachelor's/Master's degree from a reputable institution is required
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