Job Description

As the Senior Solutions Engineer, you will provide hands-on engineering support to NuCicer’s computational biology and quantitative genetics teams. Working under the direction of the Director of IT and Data Operations, you will build and maintain the cloud infrastructure, data pipelines, and analytical tools that enable NuCicer’s plant breeding programs. You will work closely with computational biologists, quantitative geneticists, and plant breeders to translate their research needs into scalable, production-ready solutions.

Responsibilities

• Deploy and maintain cloud infrastructure supporting bioinformatics and breeding analytics workloads.
• Build, optimize, and support genomic analysis pipelines (variant calling, GWAS, genomic prediction, BLUP) in collaboration with the quantitative genetics and computational biology teams.
• Support the scaling and automation of statistical and machine learning models for breedingdecision support.
• Build and maintain image processing and computer vision pipelines for UAV-captured aerial imagery, including orthomosaic generation, plot-level extraction, and trait estimation.
• Manage ingestion, storage, and cataloging of large-scale UAV and sensor datasets.
• Develop ETL/ELT workflows for biological data sources (genotypic, phenotypic, remote sensing, imagery) as directed by team leads.
• Evaluate, integrate, and maintain third-party bioinformatics and remote sensing tools and platforms.
• Maintain documentation, code quality standards, and version control practices in line with team guidelines.
• Provide technical support and troubleshooting for the team’s computational environments and scientific computing platforms.

Required Skills, Abilities and Qualifications

• 5+ years of production engineering experience, with demonstrated work in bioinformatics or computational biology environments.
• Strong proficiency in Python and at least one of R; comfortable with Bash scripting.
• Experience building and running bioinformatics pipelines.
• Containerization and orchestration (Docker, Kubernetes).
• Solid understanding of Linux/UNIX systems and cloud platforms (AWS or GCP).
• Familiarity with common genomic data formats (VCF, FASTQ, BAM/CRAM) and databases.
• Experience with SQL and at least one NoSQL or columnar data store.
• Strong communicator who can work effectively with scientists across disciplines.
• Collaborative team player comfortable taking direction while also contributing ideas and solutions.

Preferred Skills, Abilities and Qualifications

• Experience with plant breeding programs, quantitative genetics, or crop science R&D.
• Hands-on experience with genomic prediction models, BLUP/GBLUP, or marker-assisted selection workflows.
• Experience with UAV/drone data acquisition workflows and photogrammetry software (Pix4D, Agisoft Metashape, ODM).
• Familiarity with computer vision libraries and frameworks (OpenCV, PyTorch, TensorFlow) applied to plant phenotyping.
• Experience processing multispectral or hyperspectral imagery and deriving vegetation indices (NDVI, NDRE, etc.).
• Experience deploying and serving ML/AI models in production (MLflow, KubeFlow, SageMaker, etc.)
• Familiarity with remote sensing, image analysis, or digital phenotyping pipelines.
• 3+ years working with distributed or GPU computing (Spark, Dask, CUDA).
• Experience with workflow orchestration tools (Airflow, Prefect, Nextflow Tower).

Educational Requirements

• Master’s degree in Bioinformatics, Computational Biology, Computer Science, Data Science, or a related quantitative field with 5+ years of experience; OR Ph.D. with 3+ years of experience.
• Equivalent combinations of education and experience will be considered.