Machine Learning Engineer
20 hours ago
We are seeking a skilled MLOps Engineer to design and implement scalable machine learning infrastructure. This role involves building, operating, and maintaining reliable ML/LLM systems from data ingestion to model serving.
The successful candidate will partner with cross-functional teams to develop and deploy models to production while ensuring strong SLAs, observability, and cost control.
This position requires a strong understanding of machine learning lifecycles, including data versioning, feature stores, experiment tracking, evaluation, and rollback.
Required Skills and QualificationsTechnical Requirements:
- 3-7 years of experience in MLOps, Platform, DevOps, or SRE roles supporting ML in production
- Strong proficiency in Python and one of Go, TypeScript, or Bash; experience with Docker and Kubernetes
- Ci/Cd expertise with tools like GitHub Actions, GitLab, Jenkins, or Argo
- Familiarity with object storage (S3, GCS, Azure Blob), data warehouses/lakes, message queues/streams (Kafka, PubSub), and caching layers
- Monitoring and observability skills with Prometheus, Grafana, ELK/EFK, alerting (PagerDuty, VictorOps), and tracing (OpenTelemetry, Jaeger)
- Solid understanding of security fundamentals, including IAM, network policies, secrets (Vault, SSM), image signing, SBOMs
Data Science Expertise:
- Knowledge of machine learning lifecycle: data versioning, feature stores, experiment tracking, evaluation, and rollback
This role offers opportunities for career growth and professional development in the field of machine learning engineering.
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