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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

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Staff Analytics Engineer

Location: Remote
Salary: $200-250k

Are you a data expert ready to drive transformative analytics at a cutting-edge cloud platform company? This fast-growing Series C innovator is revolutionizing how teams build, preview, and deploy high-performance digital applications.

About the Role

The Staff Analytics Engineer will lead the design and implementation of robust data models and pipelines, enabling business units to uncover insights and make data-driven decisions. This role is a unique chance to collaborate with engineering, product, and business teams, building scalable analytics systems that power operational efficiency and growth.

Key Responsibilities

• Design and maintain scalable data models and pipelines to serve as a single source of truth across the enterprise.
• Develop tools to enhance data accessibility, auditing, and validation, ensuring consistent, trustworthy datasets.
• Partner with cross-functional teams to uncover actionable insights and support decision-making.
• Build self-service analytics tools and dashboards for key stakeholders, streamlining workflows.
• Collaborate on advancing the company’s data platform using cutting-edge tools like dbt, Snowflake, and Superset.
• Lead initiatives to improve data quality, governance, and discoverability, ensuring alignment with business goals.

About You

• 8+ years of experience in analytics engineering or a similar role in a modern tech company.
• Advanced proficiency in SQL, with experience working on complex datasets.
• Expertise in data platforms like Snowflake or BigQuery and transformation tools like dbt.
• Familiarity with programming languages such as Python, Java, or Go.
• Experience with BI tools like Hashboard or Superset, and a strong grasp of schema design and dimensional modeling.
• Strong communication skills and the ability to collaborate in a fast-paced environment.

Be part of a forward-thinking team where data is at the core of every decision. If you’re passionate about transforming data into meaningful insights, this role offers the chance to work on impactful projects, collaborate with top talent, and make a lasting difference.

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Staff Data Analyst, Product Analytics

Location: Remote

Salary: $200-250k

Join a rapidly growing, Series C cloud platform company recognized for innovation and leadership in modern technology. This high-impact role offers the opportunity to drive strategy, shape growth, and turn complex data into actionable insights that improve product performance and streamline operational efficiency.

About the Role

The Staff Data Analyst will play a key role in defining critical business metrics, creating scalable visualizations, and automating reporting systems. The position involves collaborating across teams to uncover insights, streamline processes, and optimize data usage to support growth.

Key Responsibilities

• Develop and implement key business metrics to measure performance and identify opportunities.
• Create dynamic visualizations and automate reporting workflows to support decision-making.
• Build and enhance analytics datasets to optimize growth strategies and reduce costs.
• Collaborate with product, business, and leadership teams to deliver data-driven solutions.
• Prototype dashboards and data tools to improve workflows and promote best practices.
• Support data accessibility by maintaining analytical technologies that ensure timely access to data.
• Shape the analytics roadmap, aligning data initiatives with organizational goals.

About You

• 6+ years of experience in a data-focused role such as Data Analyst, Product Analyst, or Business Analyst.
• Proficient in SQL and experienced in working with complex datasets.
• Familiarity with Python or R and applied statistics.
• Expertise in ELT data modeling and tools like Hashboard, Looker, or Omni.
• Strong communication skills with the ability to translate data into actionable insights.
• Adept at collaborating in a fast-paced, cross-functional environment.

This is an opportunity to join a dynamic team where data is at the core of driving decisions and innovation. If you’re passionate about transforming data into meaningful outcomes and enjoy working on high-impact projects, this role offers the chance to make a lasting contribution.

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Senior Analytics Engineer
Location: Los Angeles, CA (Hybrid)

Salary: $150-200k base

We’re partnering with a rapidly scaling, mission-focused advanced technology company operating at the intersection of AI, hardware, and large-scale systems. Their software platform aggregates and operationalizes complex, real-time data to power critical decision-making in high-stakes environments.

As the company continues to grow, they are hiring a Senior Analytics Engineer to help architect and scale the core data foundation of the business.

The Opportunity

You will design and implement the core data models that represent how the organization operates across functions such as Finance, Supply Chain, Manufacturing, People, and Operations. These models will power internal applications, workflows, and metrics used by leadership to run the business.

You’ll sit at the intersection of analytics, engineering, and operations, helping build a scalable “digital twin” of a fast-moving, technically complex organization.

What You’ll Do

• Define and develop domain-level data models that reflect real business operations
• Build secure, scalable, and extensible transformations and data pipelines
• Own ingestion and egress frameworks across multiple source systems
• Contribute to architectural decisions and roadmap direction for the data platform
• Partner cross-functionally with engineering, product, and operations stakeholders
• Translate ambiguous business questions into structured, production-grade data systems
• Drive adoption of self-serve data applications beyond traditional BI

What They’re Looking For

• 5+ years of experience in Analytics Engineering, Data Engineering, or highly technical analytics roles
• Advanced SQL skills and strong experience with Python or similar languages
• Demonstrated success building scalable, reusable data models in fast-paced environments
• Experience with modern data stack tools such as dbt, Redshift, and BI platforms; exposure to enterprise data platforms is a plus
• High degree of ownership and comfort operating autonomously
• Strong communication skills and ability to partner with non-technical stakeholders
• Ability to obtain and maintain a U.S. Secret security clearance

This is a high-impact opportunity to shape foundational data systems inside a company solving complex, real-world problems at scale. If you’re excited by building data applications that influence how an organization operates, click apply to learn more.

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Job Title: Staff Data Scientist

Location: Remote (US Only)

Salary: $200-250k base + equity

About the Company:

Join a mission-focused organization dedicated to revolutionizing global education by providing innovative learning experiences beyond the traditional classroom. The company’s app is widely used across U.S. schools and impacts millions of children worldwide.

Their team is made up of talented and creative professionals with backgrounds in education and top consumer internet companies such as Instagram, Netflix, Dropbox, Stripe, and Uber. They cultivate an environment where top talent can thrive. If you’re eager to work with some of the best minds in the industry, we encourage you to apply!

Position Summary:

As a Staff Data Scientist, you will be a key player in developing the world’s leading consumer education platform. You will be part of a high-achieving, cross-functional team working closely with product, engineering, and design to shape the company’s strategic direction and tackle challenging product and business issues.

Key Responsibilities:

• Utilize data-driven insights to inform decisions and drive our brand toward new milestones
• Work collaboratively with various teams to discover user insights and pinpoint essential product improvements
• Design and analyze AB/multivariate tests to derive actionable conclusions that boost user engagement
• Lead data science projects, influencing strategic choices and addressing complex problems

Your Skills and Experience:

• 8+ years of experience in data science and product analytics
• Experience in the consumer technology sector
• Proficient in writing efficient SQL queries for large datasets
• Skilled in designing and analyzing A/B tests
• Strong understanding of growth strategies for consumer products
• Experience working in fast-paced startup environments
• Excellent verbal and written communication skills
• Strategic thinker with a keen focus on product development
• Innovative approach to using data to drive product strategy

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Staff Data Scientist, Finance – Consumption Forecasting

Location: San Francisco or New York | Hybrid (3 days per week in office)

Salary: $240-300k base + bonus + equity (RSUs)

This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.

As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.

What you’ll own

This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.

• Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
• Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
• Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
• Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
• Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
• Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
• Set forecasting best practices across the broader Data organization

What we’re looking for

• 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
• Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
• Proven track record building and productionizing ML systems at scale
• Strong Python and SQL, with experience on large-scale usage and billing datasets
• Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
• Experience partnering with Finance or executive leadership on planning cycles
• Comfortable operating autonomously in fast-moving, ambiguous environments

Nice to have

• Background in cloud infrastructure, developer tools, or consumption-based revenue models
• Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
• Prior technical mentorship or informal leadership experience

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Staff GTM Data Scientist

Location: Remote

Salary: $190-220k base

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role sitting at the heart of their product and go-to-market strategy. This isn’t a reporting role or a dashboard-builder position. It’s for someone who can drive a genuine shift toward data-driven decision making across the organization, and who has the technical depth and communication skills to bring leadership along with them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focusing on high-leverage questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to assess the real impact of product and business changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of GTM Data, acting as a strategic thought partner across Product, Marketing, Finance, and Engineering. The company is at an inflection point in how it uses data, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still maturing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

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Senior Analytics Engineer

Location: Remote

Salary: $150-170k base

We’re partnering exclusively with a fast-growing SaaS company to find a Senior Analytics Engineer to join their data team. This is a high-impact, high-autonomy role sitting at the intersection of data engineering and analytics, perfect for someone who takes pride in building data foundations that the whole business relies on.

What You’ll Be Doing

• Designing and building dimensional data models in Snowflake that underpin analytics across the business
• Developing and optimising dbt models to turn raw source data into clean, trusted datasets
• Partnering with analysts and business stakeholders to translate their needs into scalable data solutions
• Implementing data quality checks and owning the reliability of analytics datasets
• Contributing to data governance including PII handling, metadata management, and documentation
• Supporting strategic analytics across customer journeys, revenue metrics, and product usage
• Mentoring junior team members and championing best practices

What We’re Looking For

The company runs a best-in-class modern data stack built around Snowflake, dbt, and Monte Carlo, with data flowing in from Salesforce, HubSpot, Recurly, and core product databases. The team is evolving toward an AI-enabled, domain-oriented data organisation, so there’s real scope to shape the architecture, not just maintain it.

Essential:

• 5+ years in analytics engineering, data engineering, or a similar data-focused role
• Expert-level SQL: complex queries, CTEs, window functions
• Strong hands-on dbt experience
• Snowflake (or equivalent cloud warehouse: BigQuery, Redshift)
• Solid understanding of dimensional modelling and data warehouse design patterns
• Experience with SaaS metrics: MRR, churn, CLV etc.
• Python for data work or automation
• Familiarity with data orchestration tools (Airflow / MWAA)
• Comfortable working remotely and cross-functionally with distributed teams

Nice to have:

• Experience with reverse ETL tools such as Hightouch
• Exposure to BI tools (Hex preferred)
• Understanding of data mesh or domain-oriented architecture concepts

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Staff Product Analyst

Location: San Francisco (Remote Eligible)

Salary: $200K-$240K base + Equity

We’re hiring a Staff Product Analyst for a hyper-growth, Series E AI company valued at $3B+. This is an opportunity to play a key role in shaping product strategy and growth by leveraging data to drive decisions, optimize user experiences, and unlock new opportunities.

What You’ll Do:

• Shape product strategy with data-driven insights – Define key metrics, track user behavior, and identify trends that impact engagement and retention.
• Deep-dive into user journeys – Uncover friction points and growth levers to enhance adoption, conversion, and retention.
• Optimize experimentation and A/B testing – Design and analyze tests to improve product features, pricing, and personalization strategies.
• Develop self-service analytics tools – Build dashboards and automated reporting to empower teams with real-time data.
• Partner with Product, Engineering & Leadership – Translate complex data into clear, actionable recommendations to improve product performance and business outcomes.

What We’re Looking For:

• 7+ years of experience in Product Analytics, preferably within high-growth tech companies.
• Expert SQL skills and experience working with large-scale product datasets.
• Proficiency in Python or R, with a strong foundation in statistical analysis and experimentation.
• Hands-on experience with A/B testing methodologies and user segmentation.
• Experience with ELT data modeling and BI tools like Looker, Omni, or Hashboard.
• Strong executive communication skills, with the ability to influence product decisions through data.
• Thrives in a fast-paced, high-impact environment, with a passion for uncovering insights that drive product growth.

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Staff Growth Product Analyst

US Remote

$200-240k base + equity

About the Role:

We’re looking for a Staff Growth Product Analyst to drive impactful growth analytics for an innovative AI-driven development platform that’s transforming how developers create and deploy user interfaces. Leveraging cutting-edge AI technologies, this platform enables rapid prototyping and significantly accelerates product development, enhancing user growth, engagement, and overall developer experience.

Role Highlights:

• Deep dive into user behaviors, journeys, and growth funnels to uncover opportunities for enhanced engagement and acquisition.
• Generate actionable insights aimed at boosting critical growth metrics like DAU, MAU, and user retention.
• Design, execute, and analyze A/B tests to drive informed decision-making and product improvements.
• Influence strategic decision-making through rigorous data analysis and compelling recommendations.
• Collaborate cross-functionally with product managers, engineers, data scientists, and growth marketers to drive continuous product improvement and iteration.

Who You Are:

• You have 7+ years of proven expertise in growth and product analytics, ideally within early-stage or innovation-driven product environments.
• You’re adept at conducting thorough funnel analyses, spotting rapid experimentation opportunities, and recommending actionable product enhancements.
• You thrive on solving complex analytical problems with high energy and intellectual rigor.
• Experienced with modern data stack (e.g., Snowflake, dbt, Preset, Hashboard, Kafka, Fivetran, Omni, Hex, Sigma, SQL, Python).
• You have previous experience (or a strong interest) in working with AI or machine learning-driven products.

Ideal Fit: You’re a driven, collaborative analytics expert passionate about influencing groundbreaking products. Excited by high-paced, innovative environments, you’re motivated by measurable impact and shaping the future of developer-focused, AI-powered technologies.

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Senior Data Platform Engineer

Location: Los Angeles, CA

Salary: $160-200k base

We’re partnering with a fast-scaling, mission-driven advanced technology company building complex software and hardware systems deployed in real-world environments. Their platform processes and operationalizes high-volume data to power critical decision-making across the organization.

They are hiring a Senior Data Platform Engineer to design and scale the core data infrastructure that supports company-wide operations.

The Role

As a Senior Engineer on the Data Platform team, you will:

• Design and build scalable data pipelines and transformation frameworks
• Own ingestion and egress systems that unify multiple operational data sources
• Develop reliable, secure data models that power internal data products and applications
• Partner with engineering, product, and operations to translate business needs into production-grade systems
• Advocate for best practices across testing, CI/CD, data modeling, and security
• Debug and optimize complex transformation pipelines in production environments

What They’re Looking For

• 5+ years of experience in data engineering or backend engineering
• Strong programming skills in Python or similar languages
• Experience with Spark, PySpark, SQL, and dbt
• Familiarity with large-scale data platforms and cloud environments (AWS, Azure, or GCP)
• Experience with containerization and modern deployment practices
• Ability to operate autonomously in fast-moving environments
• Strong ownership mindset and attention to security best practices
• Must be a U.S. Person due to export-controlled information requirements

This is a high-impact role focused on building durable data systems that directly support operational execution at scale.

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