Location: [Laguna Hills,CA / US collaborative environment]

Team: Molecular Processing & Automation

Role Overview

We are seeking a versatile Scientist to support the development and integration of our molecular and cellular platforms. This role sits at the intersection of molecular biology, cell engineering, and automation, and will play a central role in advancing scalable, high-throughput experimental systems across biology, engineering, and therapeutics programs.

The ideal candidate is a strong experimentalist with broad technical exposure—from microbial systems to mammalian cell biology—who is excited about building robust, automation-compatible workflows and contributing to next-generation, data-driven discovery platforms.

Key Responsibilities

• Contribute to building and scaling in-house automated experimental and data acquisition pipelines, enabling tight integration between wet lab workflows and downstream modeling
• Design, execute, and troubleshoot experiments across molecular biology, microbial systems (e.g., yeast), and mammalian cell engineering, with strong emphasis on reproducibility and scalability
• Develop and optimize high-throughput screening and assay platforms (e.g., yeast display, cell-based functional assays), including assay design, selection strategy, and workflow robustness
• Support and iterate on workflows for protein expression, antibody characterization, and cell-based functional validation, ensuring compatibility with high-throughput pipelines
• Work closely with engineering teams to integrate automation systems and experimental workflows, and collaborate with AI teams to enable structured, high-quality data generation
• Implement and adapt experimental protocols onto automation platforms (e.g., Opentrons, Integra, liquid handlers), including basic scripting and protocol development

Required Qualifications

• Bachelor’s or Master’s degree in Synthetic Biology, Molecular Biology, Bioengineering, Cell Biology, or related field
• At least 1-2 years (master degree holder) or 3-5 years (bachelor degree holder) of experience working in biotech industries.
• Hands-on experience in molecular cloning (PCR, Gibson Assembly, Golden Gate, etc.)
• Hands-on experience in next-generation sequencing techniques (Library preparation, purification, quantification, and sequencing, etc.)
• Strong foundation in mammalian cell biology, including cell culture and basic engineering (e.g., transfection, stable/ transient expression)
• Experience working with microbial systems (yeast preferred)
• Familiarity with protein expression or antibody-related workflows
• Strong execution ability and comfort operating in multi-step experimental pipelines
• Ability to work effectively in a cross-functional, fast-paced environment

Nice to Have / Preferred Experience

• Experience with FACS / flow cytometry–based screening or similar high-throughput selection systems
• Familiarity with data analysis or bioinformatics workflows related to screening or assay outputs
• Hands-on experience with automation platforms such as Tecan or other liquid handling systems
• Exposure to biophysical and analytical platforms (e.g., SPR, BLI, HPLC)
• Basic programming skills (Python preferred) for workflow automation, data handling, or pipeline support
• Interest or experience in AI-driven / agentic experimental systems, including structured data generation and closed-loop workflows

What We’re Looking For

• A systems-oriented experimentalist who can connect molecular biology, cell biology, and platform-level thinking
• Strong learning agility and ability to quickly pick up new tools and domains
• Execution-focused, with a bias toward building and improving workflows rather than running isolated experiments
• Comfortable working across disciplines and contributing to evolving platform architectures
• Motivated to work at the intersection of synthetic biology, automation, and AI-driven discovery

Why This Role

• Work on integrated platforms combining synthetic biology, mammalian systems, and automation
• Contribute to building high-quality biological datasets at scale
• Collaborate across biology, engineering, and therapeutics in a highly interdisciplinary environment
• Opportunity to grow into a platform-facing scientist with broad impact across discovery programs