Senior MLOps Engineer

Reposted 10 Days Ago
Be an Early Applicant
Hiring Remotely in Copenhagen, Capital, DNK
Remote
Senior level
Software
The Role
The MLOps Engineer will manage the lifecycle of ML models, build CI/CD pipelines, ensure system reliability, and collaborate with cross-functional teams.
Summary Generated by Built In

Overview

We are on a mission to ensure everyone has access to medical expertise, no matter where they are.

Half the world still lacks access to quality healthcare. Even in advanced systems, outcomes are uneven, and clinicians are overwhelmed. Medical knowledge grows faster than human capacity can keep up.

Corti exists to close that gap. Our AI platform expands access to medical expertise, reducing errors, restoring time to clinicians, and making care more affordable, accessible, and human again.

There is no quality healthcare without a quality dialogue, and no reliable AI without a strong foundation. Help us build both.

Why Corti?

Corti is the frontier lab for clinical-grade AI. We build world-leading models and infrastructure that power healthcare's most ambitious software - from EHR vendors and virtual care platforms to the health systems that care depends on. Today, Corti serves over 100 million patients annually, including the NHS.

Our flagship model, Symphony, is trained and validated on real clinical data from real patient interactions, and powers the clinical and administrative work that healthcare runs on.

We power the builders who are redefining how healthcare works, from startups creating new patient experiences to enterprises modernizing the systems that care depends on.

If you believe that AI purpose-built for medicine will define the next century of healthcare, you belong at Corti.

The Role

We're looking for an MLOps Engineer to help ensure our machine learning models run reliably and add value in production. In this role, you'll focus on monitoring, maintaining, and integrating models into products, while also helping move models into production.

What you'll be doing:

  • Own and manage the full lifecycle of both ML models and core infrastructure – from development and deployment to monitoring and continuous improvement.

  • Build and maintain robust CI/CD pipelines for both software and ML workflows.

  • Ensure reliability, scalability, observability, and security of production systems and ML infrastructure.

  • Automate deployment, orchestration, and environment management using modern DevOps tooling.

  • Collaborate closely with software engineers, ML engineers, and product teams to bring ML-powered features to production.

  • Proactively detect, troubleshoot, and resolve infrastructure and model performance issues.

  • Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering.

  • Document infrastructure, workflows, and operational procedures clearly and thoroughly.

What you bring:

  • Experience deploying machine learning models into production and managing their lifecycle

  • Experience implementing model governance, including versioning, monitoring, drift detection, and reporting

  • Familiarity with MLOps tools such as MLflow, Kubeflow, or DVC

  • Solid understanding of CI/CD systems (e.g., GitHub Actions, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm).

  • Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing.

  • Experience mentoring or supporting colleagues to help them grow their technical skills

  • Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role.

  • Strong proficiency in Python.

  • Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes).

  • Ability to design scalable, secure, and observable systems in fast-moving environments.

  • Strong debugging and problem-solving skills across distributed systems.

  • Excellent collaboration and communication skills, with experience working in cross-functional teams.

  • Understanding of security and compliance best practices for both software and ML systems.

Life at Corti

  • You will be reporting to the Director of Engineering

  • The position is full-time and starts as soon as possible.

  • Hybrid working environment in our Copenhagen Office

  • Equipment provided by Corti

Ready to dive into the world of Corti? Hit that 'Apply' button, and let's start working together on reshaping the dialogue in healthcare, making a real difference for millions of patient outcomes around the world.

🤝 Bringing in top talent from all backgrounds is crucial in our pursuit to improve the world of healthcare. We encourage applications from all people and do not discriminate based on race, religion, national origin, gender, sexual orientation, age, and/or disability status.

At Corti, experience comes in many forms, and we’re passionate about creating teams with a multitude of perspectives! If you believe your experience is close to what we’re looking for but not an exact match, we still hope you’ll consider applying!

Skills Required

  • Experience deploying machine learning models into production and managing their lifecycle
  • Experience implementing model governance
  • Familiarity with MLOps tools such as MLflow, Kubeflow, or DVC
  • Solid understanding of CI/CD systems
  • Familiarity with data engineering concepts
  • Experience mentoring or supporting colleagues
  • Proven experience in a senior-level DevOps or MLOps role
  • Strong proficiency in Python
  • Deep experience with cloud platforms and container orchestration tools
  • Strong debugging and problem-solving skills across distributed systems
  • Excellent collaboration and communication skills
  • Understanding of security and compliance best practices
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The Company
København K
102 Employees
Year Founded: 2006

What We Do

Corti offers healthcare practitioners a voice-based AI platform for analyzing patient interviews, helping them to make decisions faster, and more accurately during a medical consultation. Healthcare organizations use Corti to optimize their patient interview processes in order to save time, reduce costs, and improve patient quality of care

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