About the Role
Design and implement advanced machine learning systems to interpret complex biological datasets with a focus on scalability and real-world application.
Responsibilities
- Develop deep learning models tailored to genomic sequence interpretation
- Optimize neural network architectures for high-dimensional data
- Collaborate with research scientists to integrate AI into analytical pipelines
- Train models using large-scale biological datasets
- Improve model accuracy and inference speed
- Deploy machine learning solutions in production environments
- Evaluate emerging AI frameworks and tools
- Contribute to model documentation and reproducibility standards
- Work with distributed computing systems for training at scale
- Support validation of AI-driven insights with experimental teams
- Ensure models comply with data privacy and regulatory requirements
- Participate in code reviews and technical design discussions
- Troubleshoot performance issues in model deployment
- Mentor junior engineers on AI best practices
- Stay current with advancements in deep learning and genomics
Nice to Have
- PhD in a relevant technical discipline
- Experience in bioinformatics or computational biology
- Contributions to open-source machine learning projects
- Publications in AI or genomics conferences or journals
- Hands-on work with sequence analysis pipelines
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid or remote work options available
Team
Collaborative environment focused on advancing genomic technologies through machine learning
Why Join Us
- Be part of a mission-driven organization transforming healthcare through genomics
- Work on cutting-edge AI applications with real-world impact
What We Offer
- Flexible work arrangements to support work-life balance
- Opportunities for professional growth and technical leadership
Visa sponsorship may be available for qualified candidates
