We are rebels IONLACE is a place for rebels. We are on a mission to rewrite the timelines of breakthroughs in medicine.

You will be joining a team with experience from leading biotechnology companies and institutions across the world. You will be working at the cutting edge of machine learning and synthetic biology. We operate as a fast-paced startup with our office and lab at the Karolinska Institute in Stockholm. Join us and build the future.

About The Role We’re looking for a Senior Computational Protein Engineer who combines deep protein engineering expertise with modern machine learning. In this role, you’ll apply and evaluate state-of-the-art AI models using proprietary datasets, rigorously analyze their outputs, and help prioritize the most promising designs for rapid experimental validation. You will be independently executing the design efforts of our protein engineering projects.

Responsibilities

• Structural Bioinformatics Apply tools and methods including structure prediction, sequence design, docking, homology modeling, and physics-based simulation. Use structure-based metrics (e.g., pLDDT, RMSD, interface energies) to analyze and prioritize in silico designs.
• Data Engineering Build, clean, and annotate large biologics datasets for model training, benchmarking, and continual learning.
• Model Fine‑Tuning & Evaluation Fine-tune ML models, design meaningful benchmarks, run hyperparameter sweeps, and assess model performance across stability, affinity, and developability.
• Cross‑Functional Collaboration Work closely with ML engineers to integrate data and models into production pipelines, and with wet-lab scientists to iterate quickly on experimental feedback.
• Platform Innovation Prototype new functionality by extending model architectures and feature representations.

Qualifications Technical Expertise

• BSc in Biology, Biochemistry, or a related field and a PhD in Computational Biology, Bioinformatics, ML-for-Biology, or equivalent experience.
• Strong programming skills in Python, with a demonstrated ability to apply deep learning and classical ML to protein engineering challenges.
• Deep understanding of protein sequence and structure, with experience in 3D modeling, functional analysis, and protein-protein interaction analysis.
• Demonstrated capabilities in protein engineering campaigns and can drive outcomes individually.

Data Curation & Bioinformatics

• Experience assembling and managing large-scale biological datasets, including sequence, structure, and assay metadata.
• Familiarity with multiple sequence alignment (MSA), PDB handling, and feature extraction workflows.

ML Integration

• Hands-on experience fine-tuning ML models for protein design or related tasks.
• Comfortable working with modern MLOps stacks (Docker, Kubernetes, CI/CD, GitHub) to deploy and monitor models.

Execution & Ownership

• Proven ability to thrive in a fast-paced, ambiguous environment—taking projects from concept to production.
• Clear and effective communicator across computational and experimental disciplines.

Nice-to-Have

• Experience with generative protein design methods (e.g., diffusion models, graph neural networks).
• Contributions to open-source bio/ML projects or peer-reviewed publications in protein engineering.

Process We review applications on a rolling basis—please submit yours as early as possible. Our team aims to respond within 2 weeks.

Hiring Steps:

• Initial phone screen (15 minutes) – a short introductory call with a team member.

• Main selection process:

• Two 1:1 interviews focused on technical expertise and team fit

• A technical interview with a representative task (including a brief presentation)

• A culture fit interview, including a 20-minute presentation to a cross-functional audience

We aim to complete the full process within 4 weeks. All interviews are conducted via Google Meet. We do not use external recruiters.

IONLACE is an equal opportunity employer and we actively seek to create a diverse and inclusive workplace. We welcome applications from all qualified individuals regardless of their background.