Member of Data Staff (Analytics Engineer)

Perplexity is AI for people who expect more. This role brings that same standard to how our data team works, with AI at the center of everything we do. We're looking for someone who's been a great data scientist, analytics engineer, or data engineer: the kind of person who knows which metric actually matters, can design an A/B test that answers the real question, has gone deep on a data model because something didn't add up, and has decided that the highest-leverage thing they can do next is build AI systems that fundamentally change how data science gets done . You'll build AI agents and internal systems that can increasingly handle end-to-end analysis workflows: forming hypotheses, writing and running queries, interpreting results, and drafting recommendations with the right evaluation, review, and guardrails. You'll build the retrieval infrastructure and evaluation loops that let AI systems query the warehouse reliably. You'll create workflows that detect, diagnose, and help fix data issues before they become company-wide problems. You'll build the infrastructure that multiplies what a small data team can ship. You'll join a data team that's already using AI across its work. The next step is turning those individual workflows into scalable systems, shared tools, and an AI-native operating model that becomes a benchmark for how modern data teams work. What You'll Do Build AI agents that do data science - not just SQL copilots, but systems that can safely explore data, form hypotheses, run queries, interpret results, and generate actionable recommendations with clear evaluation and human review loops. Make AI systems query the warehouse reliably - build the retrieval infrastructure and evaluation loops that let agents use our semantic context and metadata accurately. Accelerate the AI-native data workflow - turn the best existing AI-assisted workflows into repeatable systems, reusable tools, and patterns the whole data team can adopt. Automate the data lifecycle -

About the Role The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. Key Responsibilities Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. Drive architectural decision

About the Role The Enterprise Trust & Governance team builds the control plane that lets the world’s largest organizations deploy Perplexity broadly and with confidence. Computer and our agents work across a growing share of our customers’ environments, tools, and models. For administrators, that makes precise, enforceable control essential: who can do what, with which data, through which agents, and within what usage limits. This team makes those controls easy to manage, reliable and consistent across every product, and transparent to the people accountable for them. This is a product and platform engineering role with end-to-end ownership, from shaping the architecture and policy models to shipping the experiences our customers’ administrators and security teams use every day. You’ll work across product and infrastructure teams to turn complex enterprise requirements into reusable primitives and intuitive controls. The scope spans identity and provisioning, fine-grained role-based access across connectors, tool actions, and models, customer-managed encryption keys, admin APIs, audit logs, and policy and usage controls. Strong governance helps enterprises move from pilots to company-wide rollouts and gives them the confidence to entrust agents with greater responsibility over time. Key Responsibilities Own enterprise identity and provisioning, including SSO (SAML/OIDC), SCIM, WorkOS integrations, and support for identity providers such as Okta and Microsoft Entra ID. Build the permissions platform, with fine-grained roles and permissions for connectors, tool actions, models, and model effort levels, enforced consistently across products and agent workflows. Design and ship secure, well-documented admin APIs for audit logs, members, groups, roles, and settings. Build policy controls for model and feature availability, staged rollouts, model deprecations, usage and spend limits, alerts, and cost-center allocation. Build admin-facing analytics for adoption, usage,

About the Role Chime serves millions of members on a mission to help them unlock financial progress. Growth Engineering builds the product surfaces and systems that turn that mission into measurable outcomes for members — running fast, data-informed experiments to acquire, activate, and deepen member relationships at scale. This role sits on our Early Stage Experience area, focused on the beginning of the member journey — the first experiences that turn new sign-ups into engaged, active members. It's high-volume, high-stakes work where small improvements compound, and the systems behind it have to be both quick to experiment on and dependable at scale. As a Staff Software Engineer, you'll operate as a subject matter expert and technical leader across the Growth stack. You'll shape the architecture and technical strategy for high-traffic, member-facing systems, influence product direction, and drive cross-team initiatives that measurably move growth outcomes while raising the engineering bar across the org. You will leverage the capabilities of AI and LLMs to improve the productivity of the org, personalize member experience and speed up decision making. In this role, you can expect to Lead the design and implementation of high-impact, member-facing systems across the Growth stack Set the technical vision for high-traffic systems with a scalable, forward-looking approach that meets Chime's reliability and latency standards Drive experimentation strategy and execution by building the systems and habits to test, learn, and iterate quickly — without sacrificing durability Identify and solve systemic challenges in performance, availability, and conversion-critical reliability across the Growth stack Collaborate closely with Product, Design, Analytics, and Data to shape product direction and ensure technical feasibility and excellence Mentor senior engineers, elevate engineering practices, and drive consistency in quality, architecture, and code craftsmanship across teams

About the role Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring a Staff AI/ML Engineer on our Lending and Cashflow team to lead the modeling behind cash flow underwriting and surface member insight: using members' transaction and deposit data to make fair, accurate credit decisions for people that traditional credit scores often miss. In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into the credit decisions behind products like MyPay, Instant Loans, and SpotMe. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters, and you'll set the technical direction for how Chime underwrites with cash flow data. In this role, you can expect to Lead the design, training, and deployment of deep learning and classical ML underwriting models that turn members' transaction and cash flow data into credit decisions, from approval and line assignment to loss forecasting Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one Connect model performance to member outcomes and business metrics, and use experimentation to prove impact Set the technical roadmap for Lending ML and raise the bar across the team through design reviews, mentorship, and shared standards for model development, validation, and governance Help identify where AI/ML creates measurable impact for me

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role: SoFi’s Senior Staff AI Engineer is a hands-on AI engineering role in SoFi’s growing independent risk organization. This is a critical, senior role responsible for setting the technical direction, driving execution, and ensuring the successful delivery of our most complex, production-level AI initiatives. This role will be instrumental in conceptualizing, prototyping and implementing best-in-class AI-based solutions to meet risk management and compliance requirements. This hands-on role will work closely with the Director of Risk Analytics, and will leverage your deep expertise to solve our hardest problems, mentor the next generation of engineers, and directly connect technical innovation to major business success. This is a crucial role for the independent risk function as we execute our mission to help more members get their money right. What you’ll do: Architecture and Strategy: Define the long-term technical architecture and strategy for our next-generation AI platform, particularly focusing on robust, scalable agentic frameworks and LLM deployment patterns. Advanced LLM Orchestration: Architect and standardize the use of graph-based LLM orchestration, leveraging expert-level mastery of LangGraph to solve highly complex, multi-stage reasoning problems at scale. Distributed Agent Memory &