About the role
Inari is seeking a Staff Machine Learning Engineer to join our AI Team in support of our mission of transforming agriculture through predictive design and advanced gene editing. This role will focus on delivering production‑ready ML pipelines using existing models while also exploring new modeling approaches to advance our ability to drive step‑change trait improvement in crops. As an individual contributor at staff level, you will drive major workstreams with autonomy while collaborating closely with cross‑functional teams of computational biologists, software engineers, and crop scientists.
Responsibilities
- Build, deploy, and maintain production ML pipelines and infrastructure to serve predictions at scale, including model versioning, monitoring, and lifecycle management.
- Integrate ML systems with genomic, phenotypic, and biological data platforms using AWS and containerization technologies.
- Partner with computational and experimental biologists to contextualize heterogeneous biological data and drive research‑critical modeling programs.
- Train and validate statistical and ML models; prototype new approaches and evaluate feasibility for production deployment.
- Implement integrations with strategic third‑party tools, foundation models, and AI agents; stay current with ML research to identify applicable methods.
- Drive major workstreams autonomously while collaborating effectively with teammates and cross‑functional stakeholders.
- Communicate technical results clearly across disciplines and contribute to technical decisions, code reviews, and engineering standards.
Qualifications
- Required education and experience: MS or PhD in Computer Science, Engineering, Statistics, Mathematics, Computational Biology, or related field (or BS with equivalent experience); 6+ years of ML engineering experience with an emphasis on production systems.
- Production ML: Proven ability to deploy, maintain, and monitor ML models and pipelines at scale.
- Python & frameworks: Advanced scientific Python (NumPy, Pandas, scikit‑learn) and hands‑on experience with PyTorch and/or TensorFlow, including training and deploying neural networks.
- Cloud & MLOps: Experience with AWS (EC2, S3, SageMaker), containerization (Docker), experiment tracking (MLflow), and workflow orchestration (Airflow or equivalent).
- Cross‑disciplinary collaboration: Comfortable interfacing with biologists and life scientists, translating between biological and ML framings, and communicating technical results to diverse audiences.
- Ownership & drive: Track record of owning solutions and deliverables end‑to‑end—setting direction, aligning stakeholders, and seeing work through to impact—while remaining a collaborative and engaged team member.
- Strongly preferred: Familiarity with biological data types (genomic, transcriptomic, proteomic), common file formats (FASTA, GFF, VCF, BAM), and sequence modeling methods applied to DNA/RNA/protein data; awareness of current research in applying deep learning to biological sequences (e.g., genomic transformers, protein language models); experience with graph neural networks or network analysis tools for modeling complex biological relationships.
Benefits
- Competitive salary range: $148,530 – 204,250.
- Compensation includes base, short‑term incentive, and long‑term equity with a one‑time new hire stock option grant.
- Comprehensive benefits package: PPO and HDHP with company‑funded HSA, vision, dental, flexible spending accounts, voluntary benefits, and a robust wellness program.
- 401(k) plan with company matching and flexible paid time off.
- Hybrid work model: weekly split between in‑office and remote work.
Inari is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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