Top Scientist Jobs in San Francisco, CA

Lead research into identity verification and fraud prevention, including detecting manipulated documents, AI-generated images, and emerging attacks. Design rigorous experiments, evaluate model performance across populations, analyze noisy and limited-label data, calibrate confidence, and identify meaningful fraud signals. Partner with machine learning and engineering teams to productionize research prototypes and publish findings at leading conferences.

Conduct research on identity verification and fraud prevention, including detecting manipulated documents, AI-generated images, and emerging attacks. Evaluate model performance across populations, identify fraud signals, calibrate confidence, and measure events with limited labeled data. Partner with machine learning and engineering teams to productionize research, publish findings, and communicate experimental results. Expertise may focus on computer vision, mathematics and statistics, or identity and fraud prevention.

Leads outsourced biologics drug product formulation and process development through CDMOs. Serves as the primary technical liaison, overseeing studies, technology transfer, manufacturing support, data packages, investigations, risk management, governance, and technical deliverables. Partners with internal cross-functional teams and external vendors to align strategy, resolve issues, manage documentation, and ensure compliant execution. Provides technical leadership, influences decisions across matrix organizations, mentors scientists, and may lead internal drug product development programs.

Lead pilot-scale cell culture operations for biologics development and toxicology material generation using shake flasks, Wave systems, and 100L/500L single-use bioreactors. Support process scale-up, technology transfer, facility readiness, data analysis, batch records, investigations, SOPs, training, and biologics manufacturing innovation. Collaborate cross-functionally to improve capacity, efficiency, compliance, and clinical development timelines.

Conduct rodent in vivo pharmacokinetic and ADME studies supporting preclinical drug development. Responsibilities include animal ordering, dosing, anesthesia, monitoring, sample and tissue collection, documentation, research animal treatment, vivarium support, and inspection readiness. The role requires independent work, collaboration with veterinarians and research teams, strong animal welfare practices, accurate recordkeeping, and rotating weekend and holiday coverage.

Own the reliability and quality of an AI copilot for trading platforms. Build evaluation frameworks, benchmarks, quality gates, monitoring, incident response, and model improvement loops. Partner with engineering and product on safe tool interactions, auditability, and user trust. Develop trading-domain expertise and measurement systems covering correctness, safety, latency, regression risk, and workflow performance.

Develop end-to-end reinforcement learning post-training for large language models operating across decentralized, high-latency consumer hardware. Responsibilities include building rollout ingestion, reward computation, policy updates, weight synchronization, asynchronous and off-policy algorithms, evaluation systems, and public model releases. The role requires strong Python and PyTorch engineering, hands-on RLHF/RLVR experience, and research ability in distributed or asynchronous reinforcement learning.

Develop efficient algorithms and systems for verifying untrusted decentralized training and inference. Responsibilities include modeling threats such as poisoning, free-riding, data extraction, and reward manipulation; designing statistically calibrated tests with controlled error rates across heterogeneous hardware; and deploying verification services in production inference systems.

Build and optimize decentralized distributed pretraining systems for frontier-scale models across heterogeneous consumer GPUs and unreliable internet connections. Responsibilities include model, data, and pipeline parallelism; communication optimization; elasticity and fault tolerance; checkpointing and recovery; and monitoring throughput, bottlenecks, and model quality. The role requires hands-on PyTorch distributed training experience, strong production Python engineering, and demonstrated execution through shipped systems, research code, open-source work, or substantial projects.

Build and own a geo-distributed inference stack for reinforcement learning rollouts and future model serving. Responsibilities include pipeline-parallel execution, routing, transport, serving-engine development, failure handling, and designing algorithms for consumer hardware connected over unreliable public networks. The role requires hands-on experience shipping inference systems, research ability in distributed inference or adjacent fields, and expertise with low-bandwidth, high-latency networking.

Leads the design, development, and deployment of scalable AI, generative AI, and machine learning solutions. Oversees data infrastructure, integration, data quality, and advanced analytics while managing client engagements and executive relationships. Drives business development, strategic direction, innovation, and AI-driven automation. Mentors teams, develops future leaders, and fosters collaboration, integrity, and client satisfaction across complex projects.

Leads AI and GenAI data science workstreams for client engagements. Develops machine learning, deep learning, and NLP models; applies statistical and predictive modeling; designs scalable data science workflows and pipelines; evaluates model performance; communicates insights through visualizations and executive narratives; coaches teams; and supports responsible AI governance.

Develops, characterizes, and qualifies human-relevant stem cell, iPSC, organoid, 3D tissue, and other complex in vitro models for drug discovery and translational safety. Responsibilities include cell culture and differentiation, assay development, experimental design, imaging and molecular characterization, data analysis, troubleshooting, documentation, and cross-functional collaboration. The role emphasizes ocular models such as retinal, RPE, vascular, organoid, and co-culture systems.

Leads strategic clinical development for investigational immunology compounds, including trial design, execution, monitoring, analysis, regulatory filings, and publications. Evaluates translational research, supports pipeline decisions, collaborates cross-functionally with regulatory, statistical, commercial, and manufacturing teams, and supervises clinical scientists. Requires advanced medical training, clinical and industry drug-development experience, and expertise in rheumatologic clinical trials. Travel is approximately 20%.

Own end-to-end computer vision and deep learning research for automated construction drawing takeoff and estimation. Develop object detection, segmentation, structured extraction, and multimodal models using visual layout, geometry, and text. Design evaluation frameworks, determine effective data strategies, assess current research, and deploy models to production. The role requires strong Python and PyTorch expertise, GPU and distributed training experience, and practical computer vision research depth.

Develops and scales small-molecule drug substance processes from early development through commercialization. Evaluates synthetic routes, controls impurities, supports scale-up and manufacturing, transfers processes to CDMOs, reviews batch documentation, troubleshoots production issues, and contributes to regulatory submissions. The role collaborates cross-functionally with manufacturing, logistics, planning, quality, and regulatory teams, while serving as a technical subject matter expert.

Lead the development and deployment of Physical AI and robotics systems for autonomous lab automation. Build 3D perception, motion planning, digital twins, simulation, multimodal vision models, edge inference, visual servoing, and closed-loop control systems. Integrate robotic hardware and laboratory APIs while validating sim-to-real performance and anomaly recovery for sustained operation in drug discovery workflows.

Identify therapeutic opportunities and prioritize targets using human genetics, multi-omics, patient data, disease biology, and clinical evidence. Evaluate target causality, safety, patient subsets, competitive landscape, and platform fit for antibody and protein therapeutics. Develop concise strategic recommendations, monitor emerging science, use AI tools for multimodal data analysis, and lead discovery programs or platform initiatives across disciplines.

Leads hands-on CHO cell line development and molecular biology projects to improve recombinant antibody expression and mAb titer. Designs vector constructs, engineers host cells, performs transfections and clone-generation campaigns, conducts gene copy and RNA analyses, measures titers, interprets CLD instrumentation data, and presents findings. Authors technical reports, collaborates across development functions, maintains equipment, and independently drives experimental design, execution, and data interpretation in a biologics CMC environment.

Leads analytical development and quality control activities for IND-enabling and early-phase clinical studies. Develops and validates methods, characterizes drug substances and products, manages stability programs, investigates deviations and out-of-specification results, and oversees analytical work at internal and external partners. Reviews technical documentation, establishes specifications and control strategies, supports regulatory filings, and ensures cGMP and SOP compliance. The role is onsite in Brisbane, California, with domestic and international travel.

Leads preclinical research supporting discovery and development of long-acting HIV therapeutics. Develops and optimizes cell-based virology and immunology assays, evaluates targets and therapeutic strategies, analyzes experimental data, collaborates with internal teams and external CROs, supports regulatory and scientific documentation, presents research findings, and mentors junior scientists.

Lead complex modeling projects combining deep learning, LLMs, and traditional techniques. Prototype, deploy, and monitor production models, mentor data scientists, collaborate with engineering/product, and translate results into business impact for insurance customers.

Embedded Data Scientist for Superhuman Mail, partnering with product, growth, engineering, and design teams to guide roadmap decisions. Responsibilities include defining product metrics, designing experiments, applying causal inference and machine learning, measuring AI feature quality, analyzing activation and retention, identifying growth and conversion drivers, and communicating insights to stakeholders. The role requires strong Python, SQL, experimentation, statistics, and cross-functional influence skills.

Performs high-complexity clinical laboratory testing, including patient sample processing, result analysis, reporting, QC, calibration, troubleshooting, corrective actions, and regulatory compliance. Maintains laboratory records and confidentiality, supports proficiency testing and quality assurance investigations, trains employees, develops procedures, and uses LIMS and molecular testing techniques. Works Tuesday through Saturday under the direction of the Clinical Laboratory Manager.

Build and scale first-line risk control monitoring systems using statistical analysis, automated workflows, and reusable data science modules. Define risk metrics, investigate control performance, establish thresholds and guardrails, and translate analyses into monitoring applications. Partner with risk, compliance, product, and engineering teams to improve governance, identify monitoring gaps, and support decision-making. Lead ambiguous, cross-functional initiatives while communicating findings, limitations, and recommendations to technical and executive stakeholders.