Machine Learning Infrastructure Engineer (Predictive Chemistry)

About us

Nexer Czech Republic is a division within DANIR AB an IT consulting and R&D company. We work with worldrenowned brands from Scandinavia the USA the UK and Western Europe. Our focus is on growing strong in competencies rather than in numbers.

If you like what we do see our offer maybe it is you we will have the pleasure to meet! :)

About the Project

Our client is an AIdriven Pharma-Tech American company focused on discovering designing and developing better medicines using advanced data science. The team is building scalable and maintainable enterprisegrade solutions used in precision cancer medicine.

What You Will Do

Nexer is seeking a Machine Learning Infrastructure Engineer to join the ML-Driven Predictive Chemistry team for a 9-month maternity cover. This team is at the heart of our drug design platform leveraging massive internal datasets and high-performance computing to accelerate the discovery of new medicines.

In this role you will bridge the gap between high-level chemistry modeling and robust engineering. You will be responsible for ensuring our predictive models are not just research-grade but production-ready scalable and deeply integrated into our automated drug design workflows.

Key Responsibilities
1. Infrastructure & Platform Engineering

• Productionize Models: Build and scale the infrastructure required to deploy state-of-the-art models (GNNs Transformers) for chemistry and structural biology.

• Data Architecture: Manage and optimize Cloud-Native Data Warehouses (BigQuery/Snowflake) to handle petabyte-scale molecular data ensuring high-concurrency access for analytical workflows.

• Pipeline Orchestration: Design and maintain robust data and ML pipelines using Argo or Prefect to ensure reproducible model training and inference.

• Active Contribution: Develop train and deploy cutting-edge predictive models within our specialized chemistry modeling platform.

• Scalable Compute: Utilize Anyscale/Ray to manage distributed training and inference workloads across massive GPU clusters.

• Agentic Systems: Architect and maintain LLM-based agentic systems to automate complex drug design reasoning and decision-making tasks.

• Cross-Functional Partnership: Work closely with the core ML Infrastructure team to ensure chemistry-specific tools align with broader company engineering standards.

You might be the perfect match if you are/have:

• Programming: Mastery of Python and its scientific ecosystem (PyTorch NumPy Pandas).

• AI Coding Agents: Modern software development practices scaffolded by AI-coding agents for production purposes including documentation unit testing formatting etc.

• ML Ops & Infra: Proven experience building and maintaining production-grade Machine Learning infrastructure (Model registries feature stores and deployment patterns).

• Workflow Orchestration: Experience with container-native orchestration tools like Argo Workflows or Prefect.

• Cloud Data Warehousing: Hands-on experience with BigQuery or Snowflake optimizing complex SQL queries and managing large-scale analytical tables.

• Cloud Ecosystem: Familiarity with modern cloud environments (GCP preferred) and Kubernetes.

• Soft Skills: Exceptional cross-functional communication; the ability to explain infrastructure trade-offs to research scientists.

• Located in Czechia Slovakia or Hungary

• Fluency in English (spoken and written)

Nice to have:

• Domain Expertise: Background in cheminformatics (RDKit molecular featurization) or biological modeling.

• Distributed Systems: Experience with Anyscale/Ray for distributed computing.

• Agentic Frameworks: Experience building or deploying autonomous agents using LLMs

Assignment Details

• Start date: ASP 2026

• Workload: full-time

• Location: Czechia Slovakia or Hugary (remote within these countries only - please note that candidates outside of these countries will be not considered)

• B2B contract

• Client: global USbased lifescience company

Recruitment process:

1. Screening Call
   A 30minute introductory Teams video call with our recruiter Nikola Otáhalová.

2. Technical Interview
   A 60minute Teams video call with one of our software developers focused on technical questions related to the required tech stack.

3. Final Interview with the Client
   A 60minute Teams video call with the client.

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