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Lead / Principal Machine Learning Engineer – Remote

The Company

A well-established technology scale-up using machine learning to power personalised digital advertising and customer engagement. With international operations and continued growth, they offer a collaborative environment where ML engineers own products end-to-end and influence key business decisions.

The Role

• Define technical direction across machine learning and MLOps
• Build and optimise recommendation, bidding, attribution, and audience targeting models
• Lead model monitoring, automated retraining, experimentation, and production ML systems
• Improve scalability, reliability, and real-time model performance
• Partner with engineering and business leaders to align ML initiatives with commercial goals
• Mentor senior engineers and drive technical best practice

Your Skills & Experience

• Strong experience building and deploying machine learning systems at scale
• Expertise with Python and modern ML frameworks such as PyTorch or TensorFlow
• Experience with recommendation systems, LTV/churn modelling, attribution, or targeting models
• Strong understanding of MLOps, model lifecycle management, and production environments
• AdTech, programmatic advertising, DSP, or real-time bidding experience highly desirable

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Staff Data Scientist (Product)

Location: Remote

Salary: $190-220k

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role embedded in their product organization. This is for someone who combines deep statistical expertise with the ability to influence how an entire company makes decisions – not just someone who runs experiments, but someone who builds the culture and infrastructure around them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focused on high-leverage product questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to measure the real impact of product 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 meaningful 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 Product Data, acting as a strategic thought partner across Product, Engineering, Finance, Design, and Product Marketing. The company is at an inflection point in how it uses data to make product decisions, 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 developing

Nice to have:

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

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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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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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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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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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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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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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Product Marketing Manager – Mobile Gaming

Location: Miami, FL (Hybrid)

Salary: $140,000-170,000

Job type: Full-time, Permanent

We’re partnering with a leading mobile game studio in Miami, part of a major international gaming group, to hire a Product Marketing Manager for its flagship title.

This is a rare opportunity to own the full player journey for one of the most recognizable games in its genre, from first ad impression to long-term retention, and turn new content launches into viral cultural moments.

Why This Role?

You’ll be the bridge between the development team and millions of players, owning full-funnel marketing strategy for a chart-topping mobile game. You’ll shape how new features and content packs go to market, drive aggressive organic growth, and lead expansion into new international markets, with real budget ownership and cross-functional influence from day one.

What You’ll Be Doing

• Define target audiences using player data, user research, and community insight, and dig into what’s driving unexpected player trends
• Shape product positioning and brand narratives that turn content updates into must-play moments, backed by competitive analysis and market research
• Design and execute full-funnel go-to-market (GTM) plans that integrate product features with user acquisition (UA), owning budgets and success metrics along the way
• Lead user acquisition and retention campaigns across paid, organic, PR, social, and non-traditional channels, including live events, influencer partnerships, and referral programs
• Build co-marketing and collaboration strategies with influencers, IPs, and consumer brands, coordinating cross-functional teams across product, paid UA, data science, and creative
• Partner with ASO and creative teams to optimize the App Store funnel, listings, and featured placements
• Own CRM and lifecycle marketing strategy to keep every player segment engaged
• Measure marketing impact through incrementality analysis, brand lift studies, and marketing mix modeling (MMM), using the data to optimize spend

What You’ll Bring

• 5+ years of product marketing experience in gaming or entertainment (mobile gaming strongly preferred)
• Bachelor’s degree or MBA in Marketing or a related field
• A proven track record of product marketing strategies and activations that delivered measurable growth
• Fluency in mobile gaming metrics (LTV, retention curves, ROAS, CPI) and the ability to turn analytics into action
• Strong cross-functional leadership: you can align developers, data scientists, and creatives around one goal
• A genuine passion for games and a sharp read on industry trends and the psychology of player engagement

To Apply for this Job Click Here

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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 Data Engineer

San Francisco, CA

$240K-$300K base + equity

We’re partnered with one of the most recognized developer platforms in the world, trusted by engineering teams at OpenAI, Meta, Netflix, and Adobe, who are scaling their data platform and looking to hire a Senior Data Engineer to own the pipelines and foundations at the core of their data ecosystem.

You’ll own the full pipeline lifecycle, from ingestion architecture through to analytics-ready data, working closely with Data Platform Engineers and partnering with analysts and data scientists who depend on what you build every day.

What You’ll Do

• Design and build scalable ingestion pipelines and orchestration frameworks across structured, semi-structured, and event-based sources
• Own reliability, observability, and performance across the full pipeline lifecycle from raw ingestion to analytics-ready delivery
• Build and maintain dbt transformation pipelines serving as the single source of truth across Finance, Product, GTM, and Engineering
• Ensure revenue and billing data meets the accuracy and auditability required for public company reporting, including SOX compliance
• Apply software engineering principles throughout: CI/CD, testing, observability, version control, and automation
• Enable self-serve analytics through semantic layer development, strong abstractions, and clear documentation
• Champion data quality and governance across classification, ownership, access policies, and data lifecycle management

What We’re Looking For

• 8+ years in data engineering or a hybrid data/analytics engineering role, with a track record of owning pipelines end-to-end in high-growth or enterprise environments
• Advanced SQL and dbt (Core or Cloud), Snowflake or comparable cloud data warehouse, Python, and Airflow
• Deep experience with Kafka and streaming data systems, with strong working knowledge of ClickHouse, Iceberg, or similar technologies
• Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
• Cloud-native architecture expertise across AWS, GCP, or Azure
• Experience designing and scaling data systems to support petabyte-level workloads
• Track record of building data infrastructure that meets compliance and governance requirements, including SOX or equivalent
• Strong communication and collaboration skills, with the ability to operate as a senior technical voice across engineering and business stakeholders

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