Join Causaly: MLOps Engineer Job Opportunity

About Us

Founded in 2018, Causaly accelerates knowledge acquisition and insight development in Biomedicine. Our production-grade generative AI platform for research insights and knowledge automation empowers thousands of scientists to discover evidence from millions of academic publications, clinical trials, regulatory documents, patents, and other data sources in minutes. We collaborate with some of the world's largest biopharma companies and institutions on diverse use cases including Drug Discovery, Safety, and Competitive Intelligence. Read more about our mission and impact on our .

We are proudly supported by top venture capitalists such as ICONIQ, Index Ventures, Pentech, and Marathon.

About the Role: MLOps Engineer

The MLOps Engineer will design, develop, and maintain the infrastructure and tools that support our machine learning models. Working closely with data scientists, engineers, and product teams, you will ensure the smooth operation of our ML workflows, from data ingestion to model deployment.

Responsibilities:

• Design, implement, and maintain our ML infrastructure, including data pipelines, model training, and deployment workflows.
• Develop and maintain tools for automating ML workflows, including data pre-processing, feature engineering, and model evaluation.
• Collaborate with stakeholders to optimize model performance, scalability, and reliability in production, including monitoring, logging, and troubleshooting.
• Develop and maintain data quality checks and data validation pipelines.
• Implement and maintain data versioning and data lineage tracking.
• Stay up-to-date with the latest developments in MLOps and recommend best practices and new technologies to the team.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Applied industry experience in MLOps, DevOps, or a related field.
• Excellent programming skills in Python, with experience in ML frameworks.
• Experience with containerization.
• Experience with data pipelines, data warehousing, and ETL processes.
• Experience with data versioning and data lineage tracking.
• Strong understanding of ML model deployment, scaling, and management.
• Excellent problem-solving skills with the ability to debug complex issues.
• Strong communication and collaboration skills, with the ability to work with cross-functional teams.
• Experience with agile development methodologies and version control systems such as Git.

Preferred Qualifications:

• Experience with MLOps platforms such as MLflow, TensorFlow Extended (TFX), or Kubeflow.
• Experience with DevOps tools such as Jenkins, GitLab CI/CD, or CircleCI.
• Experience with BigQuery.

Benefits:

• Competitive compensation package.
• Private medical insurance (underwritten on a medical health disregarded basis).
• Life insurance (4 x salary).
• Individual training/development budget through Learnerbly.
• Individual wellbeing budget through Juno.
• 25 days holiday plus public holidays and 1 day birthday leave per year.
• Hybrid working (home + office).
• Potential for real impact and accelerated career growth as an early member of a multinational team building a transformative knowledge product.

Be Yourself at Causaly

At Causaly, we value difference. Everyone belongs. Our dedication to diversity, equity, and inclusion shapes how we work together, build teams, grow leaders, innovate, and connect with the customers and communities we serve.

We are on a mission to accelerate scientific breakthroughs for all humankind and are proud to be an equal opportunity employer. We welcome applications from all backgrounds and fairly consider qualified candidates without regard to race, ethnic or national origin, gender, gender identity or expression, sexual orientation, disability, neurodiversity, genetics, age, religion or belief, marital/civil partnership status, domestic/family status, veteran status, or any other difference.

Company name: Causaly

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