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Protein Engineering Jobs in Seattle, WA (NOW HIRING)

Uw

Research Scientist/Engr 4

Seattle, WA

$122K/yr

Duties and Responsibilities: 20% Structure-based and machine-learning immunogen design for protein subunit and mRNA vaccines based on viral surface glycoproteins (construct design, recombinant ...

Uw

Research Scientist/Engineer 1

Seattle, WA

$70K/yr

Additional Requirements: 1. Programming & data: Python (numpy/pandas), basic R (Seurat/tidyverse ... Desired Requirements: 1. Probabilistic modeling: scVI/scANVI/totalVI for RNA and RNA+protein ...

Albert Invent

Software Engineer, ML Platform

Seattle, WA · On-site

$140 - $215/hr

The company is leading the development of generative AI models to design protein and antibody ... backend engineering of control plane APIs. Our ideal candidate has an opinion about slurm or ...

New

Amazon

Applied Scientist, Special Projects

Seattle, WA · On-site

BASIC QUALIFICATIONS - PhD in computer science, machine learning, engineering, or related fields ... protein biology. Amazon is an equal opportunity employer and does not discriminate on the basis of ...

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Showing results 21-40

All JobsProtein Engineering JobsProtein Engineering Jobs in Seattle, WA

Protein Engineering information

See Seattle, WA salary details

$37K

$71.7K

$108.7K

How much do protein engineering jobs pay per year?

As of Aug 19, 2026, the average yearly pay for protein engineering in Seattle, WA is $71,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,500.00 and $81,900.00 per year, depending on experience, location, and employer.

What is protein engineering?

A Protein Engineering job involves designing, modifying, and optimizing proteins for specific applications in medicine, biotechnology, and industry. Scientists in this field use computational modeling, directed evolution, and genetic engineering to enhance protein functions. Roles may include developing enzymes for drug production, improving therapeutic proteins, or creating biomaterials. This work often requires expertise in molecular biology, biochemistry, and structural biology.

What are the typical daily responsibilities of someone working in protein engineering?

A typical day in Protein Engineering involves designing and conducting experiments to modify protein sequences, expressing and purifying proteins, and analyzing their structure or function using techniques like chromatography and spectroscopy. You will often document your results, troubleshoot unexpected findings, and present data to colleagues or project teams. Collaboration with scientists in molecular biology, bioinformatics, and structural biology is common to ensure robust experimental design and data interpretation. The role may also include literature reviews to stay updated with the latest research and participating in team meetings to plan next steps or project timelines.

What are the key skills and qualifications needed to thrive in protein engineering, and why are they important?

To thrive in Protein Engineering, you need a solid background in biochemistry, molecular biology, and genetic engineering, typically supported by a relevant advanced degree. Experience with laboratory techniques such as PCR, site-directed mutagenesis, protein expression/purification, and analytical tools like mass spectrometry or chromatography is essential. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills help you stand out in this role. These competencies are crucial for designing novel proteins, collaborating in multidisciplinary teams, and ensuring successful project outcomes in biotech or pharmaceutical environments.

How much do protein engineers make?

Protein engineers typically earn a median salary ranging from $70,000 to $120,000 annually, depending on experience, education, and location. Advanced skills in molecular biology, bioinformatics, and laboratory techniques can lead to higher compensation, especially in biotech or pharmaceutical industries.

What do protein engineers do?

Protein engineers design and modify proteins to improve their functions or create new ones, often using techniques like directed evolution and computational modeling. They work in research labs, utilizing tools such as gene editing and structural analysis to develop applications in medicine, agriculture, and industry.

What are the most commonly searched types of Protein Engineering jobs in Seattle, WA?

The most popular types of Protein Engineering jobs in Seattle, WA are:

What are popular job titles related to Protein Engineering jobs in Seattle, WA?

For Protein Engineering jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Protein Engineering jobs in Seattle, WA look for?

The top searched job categories for Protein Engineering jobs in Seattle, WA are:

Protein Engineering jobs near you
Infographic showing various Protein Engineering job openings in Seattle, WA as of August 2026, with employment types broken down into 89% Full Time, 6% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $71,670 per year, or $34.5 per hour.

Research Scientist/Engineer 1

University of Washington

Seattle, WA • On-site

Full-time

Re-posted 21 days ago

University Of Washington School Of Medicine rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

79th of 619 rated colleges and universities

Job description

Job Summary:
The University of Washington is a leading institution dedicated to fostering an inclusive environment and advancing research. They are seeking a Research Scientist/Engineer 1 to contribute to computational biology projects, focusing on developing pipelines for spatial transcriptomics and related analyses.
Responsibilities:
• End‑to‑end data processing (BCL/FASTQ → QC → counts) – 20%
• Demultiplexing, adapter/quality trimming, UMI handling, alignment/quantification; generation of MultiQC reports and run manifests.
• Spatial barcode mapping & registration – 15%
• Build/validate barcode→(x,y) maps for Pixel‑seq; error correction; join gene/protein counts to spatial coordinates; QA of mapping rates.
• Segmentation & QC – 20%
• Apply/benchmark nuclei or whole‑cell segmentation (e.g., Cellpose/StarDist/SAM); maintain curated masks and QC thumbnails.
• Downstream single‑cell & spatial analysis – 20%
• Create annotated data objects (e.g., AnnData/Seurat); normalization, clustering, label transfer; spatial neighborhood/domain analysis; multi‑omic modeling for RNA+protein where applicable.
• Pipeline automation & reproducibility – 10%
• Implement/maintain Snakemake/Nextflow workflows with containers (Apptainer/Docker), CI tests, and clear documentation.
• Project support, collaboration & reporting – 7%
• Prepare figures/tables; concise analysis memos; contribute to methods sections.
• Light server/environment maintenance & upgrades (DevOps‑lite) — 5%
• Build and update containerized analysis environments, maintain conda/uv environments.
• DevOps‑lite & data stewardship – 3%
• Maintain analysis environments/containers; basic SLURM job scripts; coordinate with IT on storage/backup hygiene.
Qualifications:
Required:
• Bachelor's Degree in CS, Applied Math, Bioinformatics, Computational Biology, ECE and one year of relevant experience with Computational biology/bioinformatics.
• Programming & data: Python (numpy/pandas), basic R (Seurat/tidyverse), bash; Git; Linux.
• NGS data processing: BCL→FASTQ demultiplexing; adapter/quality trimming; UMI handling; QC with MultiQC; alignment/quantification to reference.
• Spatial omics: Pixel‑seq barcode→(x,y) mapping concepts; creation of spatially annotated objects (AnnData/Seurat).
• Segmentation: Practical use of Cellpose/FICTURE (or similar); basic image QC.
• Single‑cell & spatial analysis: Normalization, clustering, label transfer; spatial neighborhood/domain analyses (e.g., with Squidpy/Giotto).
• Reproducibility & automation: Snakemake or Nextflow; containerization (Apptainer/Docker); clean documentation; basic SLURM job submission.
• Communication: Clear writing of READMEs, short analysis memos, and figure captions for collaboration with biologists/clinicians.
• Linux/HPC usage; Slurm job submission, resource requests, and environment management.
Preferred:
• Probabilistic modeling: scVI/scANVI/totalVI for RNA and RNA+protein integration.
• GPU experience: PyTorch/CUDA for segmentation/model inference.
• Data stewardship: DVC or equivalent data versioning; basic dashboarding/monitoring (Prometheus/Grafana).
• Domain breadth: Prior coursework/research in biochemistry or genetics; interest in medical/MD‑PhD pathways.
• DevOps‑lite: GitHub Actions CI, environment pinning, reproducible reference bundles, and runbooks.
• Experience assisting with server upgrades in collaboration with IT (CUDA/cuDNN & GPU driver stacks, Slurm client updates, module systems).
• Basic familiarity with configuration/monitoring for research workflows (e.g., Ansible basics, Prometheus/Grafana dashboards) under IT guidance.
• Storage and I/O awareness for high‑throughput data (scratch NVMe vs. bulk); performance troubleshooting for pipelines.
Company:
University of Washington is an educational institution that provides undergraduate, graduate, and research programs. Founded in 1861, the company is headquartered in Seattle, USA, with a team of 10001+ employees. The company is currently Late Stage.

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