[Hiring] Machine Learning Infrastructure Engineer @Nexer Group

Role Description

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

• 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.
• Model Deployment & ML Ops
  • 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.
• Collaboration & Innovation
  • Work closely with the core ML Infrastructure team to ensure chemistry-specific tools align with broader company engineering standards.

Qualifications

• Mastery of Python and its scientific ecosystem (PyTorch, NumPy, Pandas).
• Modern software development practices scaffolded by AI-coding agents for production purposes, including documentation, unit testing, formatting, etc.
• Proven experience building and maintaining production-grade Machine Learning infrastructure (Model registries, feature stores, and deployment patterns).
• Experience with container-native orchestration tools like Argo Workflows or Prefect.
• Hands-on experience with BigQuery or Snowflake, optimizing complex SQL queries and managing large-scale analytical tables.
• Familiarity with modern cloud environments (GCP preferred) and Kubernetes.
• Exceptional cross-functional communication; the ability to explain infrastructure trade-offs to research scientists.
• Fluency in English (spoken and written).

Nice to have

• Background in cheminformatics (RDKit, molecular featurization) or biological modeling.
• Experience with Anyscale/Ray for distributed computing.
• Experience building or deploying autonomous agents using LLMs.

Assignment Details

• Start date: ASP 2026
• Workload: full-time
• Location: Czechia, Slovakia or Hungary (remote within these countries only - please note, that candidates outside of these countries will not be considered)
• Contract: B2B contract
• Client: global US‑based life‑science company

Recruitment process

• Screening Call: A 30‑minute introductory Teams video call with our recruiter, Nikola Otáhalová.
• Technical Interview: A 60‑minute Teams video call with one of our software developers, focused on technical questions related to the required tech stack.
• Final Interview with the Client: A 60‑minute Teams video call with the client.

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