Top Scientist Jobs in San Francisco, CA

As a Senior Scientist, you will develop machine learning methods for biologics design, optimize large-molecule therapeutics, and work collaboratively with experimental teams to enhance drug development processes.

Lead the Modeling and AI Enablement function within Marketing Data Science, guiding AI strategies, model development, and governance while managing a team of data scientists.

As an ML Scientist, you'll develop and improve ML models, work on the ML stack, and innovate new approaches in NLP, Speech, and Computer Vision.

The Senior Scientist in Protein Science & Engineering will lead bioanalytical research on ADCs using mass spectrometry, mentor junior staff, and support drug development and characterization projects.

The DMPK Scientist designs and executes metabolite studies, characterizes metabolites, develops PBPK models, and collaborates across teams to support drug development in oncology.

The Applied AI Scientist will develop AI features, improve orchestration and reasoning systems, and work closely with engineering teams on production capabilities.

The role involves developing cutting-edge AI/ML models for biology, leading research strategy, and mentoring. Requires expertise in machine learning methodologies and experience in biological data.

Lead research on advanced diffusion models for text-to-video. Develop algorithms, validate ideas, collaborate on integrating breakthroughs, and publish results.

Seeking a Research Scientist to lead initiatives on alignment and post-training of video generation models, focusing on quality, safety, and human alignment.

Collaborate with enterprise clients to design, train, fine-tune, and deploy customized large reasoning models and AI agents; build scalable deployment platforms, conduct research, and align solutions to client workflows.

The role involves training and deploying state-of-the-art ML models, with ownership over research projects and familiarity with data engineering.

The Senior AI Research Scientist will research and develop models, collaborate with cross-functional teams, and engage in open-source contributions while showcasing findings in publications.

Develop and deploy computer-vision and ML pipelines for microscopy datasets, partner with biologists and engineers, benchmark and calibrate tools, extract disease-relevant phenotypes, and communicate results to cross-functional stakeholders.

Design and execute high-throughput molecular assay development studies, write SOPs and Design History File documentation, perform NGS data analysis and interpretation, implement assays for production (automation, QC, LIMS), transfer and train CLIA operators, mentor lab staff, and collaborate across automation, bioinformatics, clinical, regulatory, and marketing teams.

Design, implement, and monitor QC processes and bioinformatic analyses for high-throughput RNA-based microarray and NGS LDT diagnostic products run in CLIA labs. Develop algorithms, author SOPs and validation documentation, troubleshoot operational issues with cross-functional teams, and build dashboards/visualizations (Tableau, R Shiny) to track lab performance and identify trends.

Perform hands-on assay development and optimization for high-throughput diagnostic platforms. Design experiments, write SOPs and Design History File documentation to meet FDA requirements, transfer assays to production, troubleshoot labs, and collaborate with automation, LIMS, bioinformatics, regulatory, and clinical teams.

Lead design, development, validation, and deployment of scalable NGS bioinformatics workflows for regulated diagnostics. Drive assay study design, ML/statistical evaluation, regulatory compliance, documentation, and mentor junior team members.

The role involves building production-level machine learning models, optimizing algorithms for content delivery, and collaborating with teams to implement models. A focus on machine, deep learning, and data-driven insights is required.

The Senior AI Scientist will lead ML/AI innovation for multimodal video models, develop production-grade ML models, and engage in research and representation at conferences.

The role involves leading medicinal chemistry efforts for peptide therapeutics, overseeing research projects, optimizing drug candidates, collaborating cross-functionally, and mentoring junior scientists.

This role involves designing and generating DNA assemblies for protein engineering, utilizing display technologies, mentoring junior staff, and contributing to scientific publications.

The Data Scientist II will lead RWE studies, derive insights from real-world clinical data, and contribute to methodologies using advanced statistical techniques and AI tools, collaborating closely with pharmaceutical partners.

Responsible for designing experiments to evaluate AI models, developing evaluation methodologies, analyzing performance data, and collaborating on production insights.

The Machine Learning Scientist will lead open-source research, design experiments, develop novel methodologies, and analyze large-scale data to advance AI model evaluation and transparency.

Lead development of scalable molecular dynamics pipelines, integrating physics-based models with machine learning frameworks to enhance molecular engineering and experimentations.