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Scientist II, Cell Line Engineering
Job Location:
Job Location:
San Mateo, CA - USA
Monthly Salary:
$ 145000 - 165000
Monthly Salary:
Posted:
6 June 2026 (30+ days ago)
Posted:
Application Deadline:
3 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
The role: BigHat is looking for an energetic and motivated individual to lead cell line engineering as a core Platform capability in support of our pipeline Discovery and early R&D efforts. This is a lab based role that will report directly to the Head of Protein Sciences work cross functionally with Programs and Discovery and directly impact the identification and validation of next generation biotherapeutics engineered on the Milliner Platform.
*At BigHat we believe in titles that commensurate with skill set relative organizational impact and value contribution; more experienced candidates are encouraged to apply with the understanding that responsibilities and title would adjust as appropriate.
*At BigHat we believe in titles that commensurate with skill set relative organizational impact and value contribution; more experienced candidates are encouraged to apply with the understanding that responsibilities and title would adjust as appropriate.
Key Responsibilities
- Onboard all the core components necessary for engineering cell lines for expressing pipeline targets including expression vectors gene delivery methods selective antibiotic concentration determination protocols expression validation and cell sorting capabilities
- Culture and maintain a variety of cell types; generate diverse target cell lines including knock-outs stable cell lines overexpressing one or more targets and reporter cell lines
- Perform the validation of cell line expression using flow and sequencing (Sanger or NGS) based methods.
- Generate bulk pool and single cell populations utilizing FACS to select for cell lines of various expression levels
- Maintain an organized cell line inventory with all relevant documentation
- Investigate target expression biology to recapitulate the most native conditions for expression.
- Work with end user stakeholders to confirm correct domain expression and associated sequences
- In collaboration with end user stakeholders establish the workflows timelines and deliverables for cell line engineering from request to hand-off
- Collaborate with automation engineers to automate routine cell culture workflows to increase efficiencies and throughput
Skills Knowledge and Expertise
- PhD in biology-related discipline with minimum of 3 years industry experience preferably in an environment utilizing cell lines for antibody discovery and engineering
- In depth molecular biology knowledge for plasmid construction and experience selecting expression vectors and promoter types
- Experience culturing various cell types including adherent suspension shaker flask etc. High level of organization in handling multiple cell lines simultaneously for manipulation and maintenance
- Demonstrated hands-on success in using CRISPR/Cas9 transposon or lentivirus based technologies
- Adept with Fluorescence or magnetic-bead based cell sorting methods and clonal selection and maintenance
- Prior use of automation for cell culture a plus
Total Rewards
The salary estimated for this position is $145000 - $165000 bonus options benefits. Compensation will vary depending on job-related knowledge skills and experience. Actual compensation will be confirmed in writing at the time of the offer.
What BigHat Offers:
What BigHat Offers:
- Range of health insurance plan options through Anthem and Kaiser (monthly credit if benefit waived)
- Dental and vision coverage through Guardian
- Additional well-being benefits through Nayya OneMedical Wagmo Rula and more
- 401(k) with company match
- DTO two weeks of company-wide shutdown and 12 company holidays
- Paid parental leave
Required Experience:
IC
About Company
BigHat Biosciences designs safer, more effective biologic therapies for patients using machine learning and synthetic biology. BigHat integrates a wet lab for high-speed characterization with machine learning technologies to guide the search for better antibodies. We apply these desig ... View more
