Machine Learning Engineer (AI Platform Lead) at Artera
This leadership role is designed for a seasoned MLOps or Platform Engineer with at least 8 years of experience, specifically someone who has transitioned from g
Work type: remote
Location: Remote-US
Salary: $180,000 – $220,000/yr
Type: Full-time
Summary
This leadership role is designed for a seasoned MLOps or Platform Engineer with at least 8 years of experience, specifically someone who has transitioned from general software engineering to building the "pipes" for large-scale AI. Ideal candidates are architecture-level experts who have managed multi-node distributed training and know how to optimize GPU throughput for massive datasets (terabytes of digital pathology data).
The position offers a strong compensation package ($180k–$220k) and the flexibility of being fully remote in the US or Canada. You will be shaping the long-term vision of a startup that uses Foundation Models to personalize cancer treatment, providing a rare opportunity to lead mission-driven infrastructure development that directly impacts patient outcomes.
**You might be a good fit if you...**
* Have deep expertise in ML orchestrators like Flyte, Ray, or Kubeflow and a background in AWS/Kubernetes.
* Enjoy the "plumbing" of AI—optimizing data throughput and distributed training infrastructure rather than just tweaking model weights.
* Are comfortable in an "IAAS" (Infrastructure as a Service) mindset, building libraries and tools that make AI scientists more productive.
* Are authorized to work in the US or Canada and do not require visa sponsorship.
Job Description
About Us: Artera is an AI startup that develops medical artificial intelligence tests to personalize therapy for cancer patients. Artera is on a mission to personalize medical decisions for patients and physicians on a global scale.
As a Machine Learning Engineer at Artera, you’ll work on the AI Platform team with a focus on establishing scalable and efficient pipelines for data processing and model training. You’ll work closely with AI model developers, fellow machine learning engineers, and our platform engineering team. You’ll ensure that Artera’s model developers can rely on highly efficient, large-scale training regimes and deploy optimized models to production environments.
## Essential Responsibilities:
- Develop the long term vision and roadmap for Artera’s AI platform that will allow the company to continue to scale in terms of both increased inference volume and development workloads.
- Accountable for Artera’s ML compute infrastructure including scaling up Artera’s Foundation Model development by developing distributed training infrastructure and developer libraries.
- Build and evolve the core libraries used by AI scientists to develop, launch, and monitor AI products.
- Work with model developers to optimize GPU and CPU efficiency and data throughput of large-scale foundation models and downstream model training runs.
- Optimize Artera’s ability to store and serve terabytes of digital pathology data efficiently for the use in serving large-scale training regimes.
- Ensure that Artera’s observability infrastructure provides a clear picture of how to continue to optimize performance across our model landscape.
## Experience Requirements:
- 8+ years of industry software engineering experience
- 4+ years of industry experience in using ML orchestration frameworks such as Flyte, Ray, Kubeflow, Metaflow, MLFlow, Dagster, Argo Workflow or Prefect
- 4+ years of industry experience using one of PyTorch, TensorFlow, or JAX in Python
- 3+ years of industry experience building with AWS, Docker, and Kubernetes
- 1+ years of industry experience optimizing large-scale, high data-throughput, distributed machine learning training pipelines
## Desired:
- Experience using Terraform, SqlAlchemy
- Experience in multi-node and multi-gpu training.
- Experience deploying and maintaining infrastructure for machine learning training and production inference
- Familiarity with TorchScript, ONNXRuntime, DeepSpeed, AWS Neuron or similar approaches to inference optimization
## Work Authorization Requirement:
- This is a remote role open to candidates who are currently authorized to work either in the United States or in Canada without the need for current or future employment-based visa sponsorship. Artera does not sponsor visas for this position.
- Eligible candidates may include:
- Individuals authorized to work in the United States on a permanent basis (e.g., U.S. citizens, U.S. permanent residents), or
- Individuals authorized to work in Canada (e.g., Canadian citizens or Canadian permanent residents).
- Visa Transfers (if needed).
## Here are few posts from our teammates, partners and customer voices to highlight the work we do:
- [Artera Shapes the Future of Cancer Treatment Using Machine Learning on AWS](https://aws.amazon.com/pt/solutions/case-studies/artera-case-study/)
- [How Artera AI test allowed Bruno to avoid hormone therapy](https://www.medscape.com/viewarticle/cms-okays-payment-novel-ai-prostate-test-2024a10000u6)
- [Startups are using AI to predict responses to Cancer Drugs](https://www.wsj.com/articles/startups-are-using-ai-to-predict-responses-to-cancer-drugs-d7fb06eb)
- [ArteraAI validates its Prognostic Model in Advanced Prostate Cancer ](https://apnews.com/press-release/business-wire/prostate-cancer-medical-research-united-kingdom-41d540a7fc1e4512b4a9c1cb2d69e5e7)
- [How Artera Enhances Prostate Cancer Diagnostics Using AWS](https://aws.amazon.com/blogs/architecture/how-artera-enhances-prostate-cancer-diagnostics-using-aws/)
As a Machine Learning Engineer at Artera, you’ll work on the AI Platform team with a focus on establishing scalable and efficient pipelines for data processing and model training. You’ll work closely with AI model developers, fellow machine learning engineers, and our platform engineering team. You’ll ensure that Artera’s model developers can rely on highly efficient, large-scale training regimes and deploy optimized models to production environments.
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