Overview
Job Details
IDR is seeking an MLOps Engineer to join one of our top clients in the Healthtech-startup space (fully remote). If you are looking for an opportunity to join a large organization and work within an ever-growing team-oriented culture, please apply today!
Position Overview:
We are looking for an experienced MLOps Engineer to support the development and scaling of ML infrastructure at a cutting-edge, AI-focused startup. This role will focus on automating, monitoring, and optimizing machine learning pipelines in a cloud-native environment, primarily using GCP and Kubernetes. You’ll work closely with data scientists, ML engineers, and DevOps teams to ensure scalable and reliable deployment of machine learning models.
Required Skills:
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4+ years of experience building MLOps solutions and ML infrastructure, ideally at a large-cap, AI-driven startup
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Strong experience with GCP services, including Cloud Storage, Vertex AI, IAM, GKE, Compute Engine, and BigQuery
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Expert-level knowledge of Kubernetes, GKE, and container orchestration for ML model deployment
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Familiarity with monitoring and observability tools like Prometheus, Grafana, and OpenTelemetry
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Hands-on experience automating infrastructure with Terraform
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Experience implementing CI/CD pipelines for ML workflows (e.g., GitOps, Kubeflow Pipelines, MLflow)
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Experience supporting multi-cloud or hybrid cloud ML deployments
Nice-to-Have Skills and Experiences:
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Experience with Weights and Biases
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Experience contributing to 0-1 ML infrastructure initiatives
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Background in LLM fine-tuning and inference optimization (e.g., quantization, distillation)
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Proficiency in LLM model serving frameworks such as TGI, VLLM, and SGLANG
What’s in it for you?
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Work with cutting-edge ML infrastructure and deployment strategies
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Fully remote work flexibility
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Opportunity to shape infrastructure at an innovative, AI-driven startup
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Collaborative and forward-thinking engineering culture
Why IDR?
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Competitive compensation packages
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Industry-leading benefits
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Dedicated Engagement Manager who is committed to you and your success
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Access to a network of top employers nationwide
Compensation Details: $60-65/hr W2