Senior Platform/MLOps engineer (Cheminformatics)
Summary
Senior platform/MLOps engineer building and maintaining cloud infrastructure and platforms that support computational drug design and discovery: designing scientific workflow orchestration, building data/compute pipelines with Apache Airflow and Python, containerizing services with Docker, and automating deployment and infrastructure for AI-driven research workloads.
We have 30 years of expertise in designing and building custom software systems. We provide software development services focusing on complex high-load applications, AI and BI solutions, and mobile apps.
Modern drug discovery increasingly relies on complex computational infrastructure, scalable cloud technologies, and interconnected software systems. Building and maintaining reliable platforms that support these technologies is essential for enabling efficient, scalable, and reproducible scientific research.
We are looking for a Platform Engineer to join our team and drive the development, maintenance, and evolution of the infrastructure and platforms that support computational drug design and discovery. In this role, you will be responsible for building and optimizing cloud infrastructure, automating deployment and operational processes, and providing reliable, scalable, and secure environments for scientific applications, data pipelines, and AI-driven workflows. You will also help improve developer experience by creating reusable tools, services, and infrastructure components that enable our teams to develop, deploy, and operate software more efficiently.
Key Responsibilities
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Design, develop, and maintain scalable platforms for scientific workflow orchestration and automation.
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Build and manage complex data and computational pipelines using Apache Airflow and Python.
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Develop and maintain containerized applications and services using Docker.
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Ensure the reliability, scalability, and reproducibility of automated scientific workflows.
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Integrate different computational tools, data sources, and services through APIs.
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Collaborate with AI/ML engineers, computational scientists, and software developers.
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Contribute to infrastructure automation and continuous delivery practices.
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Optimize platform performance and support the deployment of AI-driven applications.
Requirements
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6+ years of experience in Platform Engineering, DevOps, Infrastructure Engineering, or a related field.
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Strong hands-on experience with Python.
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Practical experience with Apache Airflow or similar workflow orchestration tools.
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Solid experience with Docker and containerized environments.
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Experience designing, building, and maintaining automated workflows and data pipelines.
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Good understanding of cloud infrastructure and distributed systems.
Nice to Have
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Experience with AWS or other cloud platforms.
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Familiarity with Kubernetes.
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Experience with Terraform, GitOps, or Infrastructure as Code practices.
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Experience with PostgreSQL and Snowflake (primarily data querying and reading).
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Understanding of API design and service integration.
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Experience developing or supporting AI/ML-driven applications.
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Background in life sciences, computational chemistry, bioinformatics, or drug discovery.
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Experience with other workflow orchestration and management solutions.
Our offer as your future employer
- Collaboration via a B2B contract with payments in USD or EUR, depending on your preference, or through a labor contract
- Flexible work schedule.
- Possibility to work remotely
- Opportunities for professional growth.
- A company laptop to ensure a comfortable and efficient work setup.