a-b-testing jobs in San Diego

Staff Data Scientist leading analytics strategy for Intuit's Connected Accounts product, responsible for owning the analytics agenda end-to-end from account linking through engagement. The role requires applying ML and causal inference techniques to solve connected-accounts-specific problems, designing and running A/B tests and quasi-experimental designs, building member segmentation, and identifying AI/ML opportunities.…See more You will partner closely with Product, Engineering, and Design leadership on roadmap prioritization, mentor other data scientists, and use AI-native tools to synthesize analyses ranging from experiment readouts to churn deep dives.

Lead a high-performing Customer Experience team driving TurboTax's omni-channel assisted services across retail, virtual, and hybrid channels. Own strategy and execution for customer success initiatives, partnering with Product, Marketing, and Analytics to optimize customer journeys, drive conversion and retention, and build internal capability in design thinking and continuous improvement.…See more Analyze customer behavior data, design and validate experiments (A/B testing), and translate Voice of the Customer insights into product and business strategy. Coach managers and individual contributors while representing CX on cross-functional leadership teams and managing complex organizational change.

As an AI Science Intern, you will work alongside AI Scientists and Machine Learning Engineers to build, train, and evaluate machine learning and deep learning models on real-world datasets. Responsibilities include data gathering and ETL, feature engineering, model development using techniques like classification, regression, clustering, and neural networks, and designing experiments to measure impact.…See more You'll explore current AI/ML research including generative AI and LLMs, develop proofs-of-concept, and partner with cross-functional teams to translate insights into product features. The role requires strong Python and SQL skills, familiarity with core ML techniques and their mathematical foundations, and the ability to communicate findings to both technical and non-technical audiences.

Design and optimize video analysis, quality assessment, and encoding algorithms for hardware-accelerated video codec solutions (FPGA/ASIC). Develop C-models and firmware implementing deep learning techniques (CNNs, Transformers, MLLMs) for video processing, ROI detection, and frame-level rate control.…See more Collaborate with infrastructure teams to integrate algorithms into production VOD and live-streaming pipelines, validate performance through A/B testing, and participate in objective video quality evaluation using metrics like VMAF, PSNR, and SSIM.

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.

Build and ship production ML systems end-to-end for autonomous medical coding in a SaaS platform, from problem framing through deployment and monitoring. Own the full lifecycle—data discovery, feature engineering, training, evaluation, and iteration—working with LLMs, deep learning, and modern MLOps tooling to handle millions of medical charts daily.…See more Design robust, low-latency architectures, establish rigorous evaluation strategies, and implement model observability, drift detection, and bias assessments. Collaborate across product, data, and platform teams to translate business goals into measurable ML outcomes.

Design and optimize machine learning models for deployment on edge devices including smartphones, IoT, and automotive platforms. Build end-to-end experimentation pipelines, benchmark models on real hardware, and work with cross-functional teams to move innovations into production.…See more The role emphasizes model optimization for constrained hardware environments, hardware benchmarking, and research contributions through publications and patents.

Develop scalable AI engineering patterns and production-quality code for government clients, balancing quality, safety, latency, cost, and model risk. Apply strong practices in testing, CI/CD, logging, versioning, and documentation while designing extensible functionality aligned with senior team members.…See more Requires 4+ years of software/data engineering experience, 1+ year building and deploying GenAI or LLM solutions, and 1+ year with Google Cloud (Gemini API, Vertex AI Agent Builder, Grounding, or Google Workspace integration). Lead project workstreams, translate business problems into AI solutions, and contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

As Associate Director of Customer Engagement Platforms & Data, you will lead product management, solution architecture, and delivery for commercial and medical affairs customer engagement capabilities—including Veeva and Salesforce CRM, marketing automation, and digital engagement platforms. You will translate business and data strategies into product plans and technical requirements, partner across Commercial Systems & Analytics and Enterprise Data & Intelligence to align roadmaps and governance, and provide hands-on delivery leadership from discovery through deployment and continuous improvement.…See more The role requires balancing product ownership with technical accountability for architecture, security, scalability, compliance, and data governance in a shared operating model with cross-functional teams.

Build applied AI systems for Crucible, Firestorm's manufacturing operations software. You'll productionize ML and optimization models, integrate foundation models and LLMs into workflows, and design end-to-end AI capabilities—from model selection and evaluation through reliable production deployment across cloud, air-gapped, and edge environments.…See more This is a hands-on engineering role requiring 5+ years shipping production ML/AI systems, strong Python and software engineering fundamentals, and deep experience with LLMs, transformer models, and production ML monitoring.

Staff Quality Analyst role responsible for building dashboards and analytics that surface defect signals and drive leadership decision-making at scale. The role combines hands-on data analysis (SQL, Python, statistics) with AI-native workflows to accelerate defect detection and root cause analysis, plus structured change management to land measurement and process changes across large stakeholder groups.…See more Required skills include strong SQL/Python proficiency, applied statistics, experience with defect frameworks (DPMO), contact center operations familiarity, and demonstrated ability to communicate data findings credibly to executives and manage organizational change.

Engineering Lead responsible for hands-on ML research, model development, and production AI system deployment in a live trading environment. You will work closely with quantitative research leadership to shape and execute the research agenda, design and train models, lead day-to-day technical execution across the engineering team, and mentor engineers to raise overall technical standards.…See more The role requires 4–6 years of applied ML/AI experience with 1–2 years of technical leadership, strong proficiency in Python and PyTorch, and a track record of shipping production ML systems where model performance directly impacts real-world outcomes.

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

Design, build, and operate production ML systems across the full lifecycle—from data preparation and model training through deployment, monitoring, and continuous improvement. Partner with data scientists, software engineers, and platform teams to turn research prototypes into reliable, scalable services.…See more Work across recommendation, ranking, forecasting, classification, NLP, and generative AI depending on product priorities. Balance model quality, inference latency, scalability, and operational resilience as equally important outcomes.

As a Senior Data Scientist on PlayStation's Decision Science team, you will lead the design, execution, and interpretation of A/B tests and quasi-experiments to evaluate PS4-to-PS5 migration initiatives, growth marketing strategies, and campaign performance. You'll apply advanced causal inference methods, develop experimentation frameworks and best practices, and independently extract and analyze data using SQL and Python.…See more The role requires deep expertise in experimental design, statistical rigor, and the ability to communicate findings to drive business decisions across product, engineering, and marketing teams.

This UX Designer role shapes end-to-end experiences for a cloud-based AI platform, translating complex workflows and data into intuitive web and mobile interfaces. The designer will own discovery, interaction design, prototyping, and delivery across multiple product areas, working closely with product managers, engineers, and UX researchers.…See more Responsibilities include defining user flows and information architecture, creating high-fidelity designs in Figma with reusable components, conducting and synthesizing usability research, and contributing to a scalable design system. The role requires 3–6 years of product design experience, strong Figma proficiency, expertise in accessibility (WCAG), and demonstrated ability to collaborate across cross-functional teams in an agile environment.

Engineering Lead responsible for designing, developing, and deploying production ML models for live trading environments while leading day-to-day technical execution across the engineering team. You will work with leadership to shape the research agenda, mentor engineers, drive adoption of AI tools to accelerate engineering workflows, and build/improve core ML infrastructure including data pipelines, training workflows, and inference systems.…See more The role requires 4–6 years of applied ML/AI experience with 1–2 years leading technical projects or teams, strong proficiency in Python and PyTorch, and a track record of shipping ML systems where model performance directly impacts business outcomes.

Join Sony Interactive Entertainment's D2C Data Science team to support PlayStation's payment and subscription experiences through statistical analysis, A/B testing, and machine learning. You will own analyses of payment success, subscription recovery, and payment flow optimization, building models for forecasting, segmentation, and propensity while translating complex data into actionable recommendations for product and engineering teams.…See more The role requires strong SQL and Python skills, solid statistics and experimental design knowledge, and the ability to work independently on well-scoped analyses while communicating findings clearly to both technical and non-technical stakeholders.

Lead a team of Databricks engineers delivering GenAI and LLM solutions to government clients. You'll architect and deploy production-scale data platforms, mentor engineers, and translate business requirements into AI solutions using Databricks' full stack (Lakehouse, Agent Bricks, Model Serving, Genie, Apps).…See more Enforce strong data management, CI/CD, testing, and documentation practices while working across AWS, Azure, and Google Cloud environments.

Senior Forward Deployed Engineer at Deloitte GPS building AI-enabled solutions and agentic platforms on Databricks for enterprise government clients. Requires 7+ years software/data engineering experience, 5+ years deploying GenAI/LLM solutions in production, and 5+ years hands-on Databricks expertise across Lakehouse, Agent Bricks, Model Serving, and Genie.…See more Mentors junior engineers, designs scalable AI patterns with human-in-the-loop controls, delivers production-quality code with strong CI/CD and testing practices, and translates complex business problems into deployable AI solutions.

Lead machine learning strategy and development for AppFolio's Leasing products, owning the ML roadmap and autonomous leasing agent architecture. Build evaluation frameworks, model quality infrastructure, and establish ML standards across the Leasing Engineering team while ensuring production-grade reliability, SLOs, and observability.…See more Translate research into shipped features by evaluating fine-tuning approaches, RAG patterns, and agentic systems; operate with production discipline on a SaaS platform serving real customer workflows.

Lead ML research and production model development for a quantitative trading firm, working hands-on to design, train, and deploy ML systems that directly impact live trading environments. You will drive technical execution across the engineering team, mentor engineers to raise the bar, and translate ambiguous research problems into executable modeling work with measurable real-world impact.…See more The role requires 4–6 years of applied ML experience with 1–2 years of technical leadership, strong fluency in Python and PyTorch, and a track record of shipping production systems in high-stakes contexts.

Lead the design, development, and operation of Qualcomm's enterprise AI platform, supporting agentic AI, model lifecycle management, and multi-cloud ML/inference infrastructure. Own core platform services including identity/RBAC, secrets, service meshes, observability, vector stores, and model gateways across on-prem GPU clusters and managed cloud services.…See more Manage a ~10-engineer global team (platform, SRE, MLOps/LLMOps), drive incident response and continuous improvement, and partner with product and security teams on AI governance and high-impact use cases.

Lead product strategy and roadmap for Intuit's next-generation Agentic AI Platform, designing core execution frameworks, agent libraries, and SDKs that enable complex reasoning and autonomous task execution across TurboTax, QuickBooks, Mailchimp, and Credit Karma. Define extensible platform architecture, drive multi-step planning and orchestration capabilities, and ensure agent observability and trust at scale.…See more Partner closely with engineering and architects to standardize agent development, deployment, and management while mentoring other product managers on technical fluency and platform thinking.

Web Developer responsible for designing and implementing web applications across headless CMS, SaaS, and IaaS platforms using modern frameworks like React, Vue, and Node.js. The role involves A/B testing, UX/UI optimization, API integration, and supporting digital marketing campaigns.…See more Requires 3+ years of web development experience and proficiency with headless content management systems (Contentstack, Contentful, Sanity), REST/GraphQL APIs, TypeScript, and version control systems like Azure DevOps.