Bioinformatics Engineer

Arcus Biosciences•Hayward, CA

2d•$120,000 - $155,000•Hybrid

About The Position

Arcus is seeking a Bioinformatics Engineer to work in a highly embedded, collaborative model with colleagues across the organization. The engineer will join highly technical, interdisciplinary teams and bring a creative, problem-solving mindset to challenging work. The successful applicant will help improve and harmonize bioinformatics processes, as well as take lead in augmenting a growing internal database of multimodal, high-dimensional datasets to enable critical bioinformatics functions. They will use their expertise to build infrastructure, develop pipelines and frameworks, optimize algorithms, and process harmonized high-dimensional molecular datasets. The individual may also support cross-departmental infrastructure developments to enable effective inter-departmental information exchange and develop LLM systems (e.g., literature review agents, retrieval-augmented knowledge systems) to enable bioinformatics and drug development discoveries.

Requirements

Master’s in Bioinformatics, Computational Biology, Data Science, Computer Science, or similar field, with 5+ years of experience.
Strong understanding of data structures and transformations to enable efficient modeling.
Proven coding expertise in Unix and SQL for systems and database query and development.
Proficiency in R and/or Python for bioinformatics pipelines and analysis.
Experience with a workflow language such as Snakemake or Nextflow.
Adept at building reproducible computing environments using tools such as Docker, Singularity/Apptainer, uv, or conda.
Ability to work with on-prem and cloud-based systems including HPC clusters (e.g., SLURM) and AWS.
Fluent with version control using Git/GitHub and collaborating with other bioinformatics scientists/engineers.
Comfortable working in a cross-functional environment and handling several concurrent fast paced projects.

Nice To Haves

Understanding of high-dimensional molecular data types, such as RNA-seq, scRNA-seq, etc.
Familiarity with best coding practices such as unit testing, CI/CD, reproducible code, and modular pipeline design.
Experience developing pipelines and general frameworks for data analysis.
Ability to write concise technical documentation.
Familiarity with LLM-based tools, including LLM-assisted and agentic programming.

Responsibilities

Process and QC high-dimensional datasets to expand internal databases (e.g., RNA-seq, scRNA-seq, spatial transcriptomics, proteomics, etc.).
Maintain and improve internal pipelines for data processing, including RNA-seq and WES.
Develop standardized internal pipelines for processing of additional data types such as scRNA-seq and spatial transcriptomics.
Work closely with Bioinformatics Scientists on improving internal processes and databases to enable efficient data extraction and transformation for rapid bioinformatics analysis and visualization.
Collaborate with constituencies in IT and Scientific Computing to improve on-prem and cloud-based infrastructures to support bioinformatics functions.
Serve as the technical resource for optimizing pipelines, benchmarking algorithms, developing reproducible frameworks, and updating SOP documentation & internal knowledge base.