Scientist , Screening Tech Development

Profluent is an AI-first protein design company. Founded in 2022, we develop deep generative models to design and validate novel, functional proteins to revolutionize biomedicine. Based in Emeryville, CA, we are backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures, and have raised over $150M to date.

Profluent is seeking a highly motivated and versatile Scientist I to drive screening infrastructure development and deployment to transform our mammalian genome‑editing platform. This is a hands‑on, lab‑based role focused on bridging AI‑driven enzyme design with high‑throughput experimental validation. The successful candidate will spearhead advanced genome‑editing projects, build scalable screening workflows, and support key internal and external collaborations.

The ideal candidate will bring a strong foundation in mammalian cell biology, genome editing, molecular biology, and an eagerness to collaborate deeply with biologists, bioinformaticians, machine learning engineers, and automation teams.

• Build and disseminate scalable pooled mammalian screening and DNA preparation workflows across teams, drive the impact of said novel technologies, and manage the infrastructure required to screen large‑scale libraries
• Design, execute, and optimize high‑throughput (HTP) mammalian transfection workflows and cell‑based assays to evaluate genome‑editing outcomes, quantify genome editing via Next‑Generation Sequencing (NGS)
• Generate poly‑ and monoclonal cell lines using Homology‑Directed Repair (HDR) and lentiviral transduction
• Leverage literature insights to independently design biologically and statistically rigorous screening experiments, troubleshoot complex cell‑based assays, and pioneer new library design methodologies, staying at the forefront of the genome‑editing field
• Partner closely with Machine Learning (ML), Bioinformatics, Automation, and Biology teams to support the adoption and impact of novel screening technologies and apply them to engineer new enzyme activities and mechanisms
• Maintain meticulously clear electronic lab notebooks, SOPs, and analytical summaries to ensure highly reproducible data handoffs to data science and platform teams
• Mentor junior colleagues and routinely share findings in department meetings; serve as an active contributor to our scientific and collaborative company culture, building and maintaining tight professional relationships across departments

• PhD in molecular biology, bioengineering, biochemistry, cell biology, or a related discipline with 0–2 years of relevant industry/postdoctoral experience, an MS with 8+ years of relevant industry experience, or Bachelor's degree with 10+ years of relevant industry experience
• Deep, hands‑on competence in mammalian cell culture, maintenance, engineering, and characterization via bulk population and (experience with hard‑to‑transfect or specialized cell lines is a plus) as well as proven expertise with monoclonal isolation and characterization techniques
• Direct experience with advanced genome‑editing modalities (e.g., base editors, prime editors, recombinases, or nucleases) and the routine use of NGS to quantify editing efficiency
• Proven expertise in modern cloning methodologies (e.g., Golden Gate, Gibson assembly, pooled library preparation), complex DNA design, analysis of pooled DNA populations, and high‑volume ordering logistics
• Direct experience setting up and executing microplate‑based, automation‑compatible workflows or deep‑well HTP transfections along with a strong understanding of how to structure and track wet‑lab data for downstream computational analysis
• Strong technical judgment, attention to detail, and the ability to pivot seamlessly between diverse infrastructure projects in a fast‑paced, startup environment
• Excellent organizational, communication, and collaboration skills

• Experienced with pooled screening and demultiplexing via NGS
• Experience with flow cytometry of mammalian cells
• Experience handling and analyzing large datasets using SQL, Python, JMP, bash, or…