DATA & AI STAFFING
SAN FRANCISCO

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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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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 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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Clinical Data Scientist
San Francisco, California

Remote

$160,000 – $190,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As a Clinical Data Scientist, you’ll execute the last leg of the clinical data pipeline by transforming, cleaning, validating, and delivering high‑quality clinical datasets for pharma partners. Heavy collaboration with Clinical Ops, AI Engineering, and Data Delivery.

Role Responsibilities

• Transform raw, abstracted, and AI‑processed data into CDISC SDTM/ADaM datasets
• Program statistical outputs (tables, listings, figures) in SAS/R/Python
• Investigate data anomalies across multiple messy data inputs
• Define data dictionaries and standards before study kickoff
• Handle data in a HIPAA‑aligned manner

Key Requirements

• 2-5 years in clinical data science, stat programming, or clinical data management
• Pharma/Biotech experience
• SAS, R, Python, SQL
• Real‑world clinical data or oncology trials
• CDISC SDTM/ADaM

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About the Company

We are a rapidly growing technology organization focused on helping enterprises unlock greater value from their data through advanced artificial intelligence and machine learning solutions. Our platform empowers organizations to transform complex data assets into actionable insights by combining intelligent automation, modern data engineering practices, and intuitive user experiences. We work with some of the most sophisticated data environments in the world and are building the next generation of AI-powered enterprise software.

The Opportunity

As an AI/ML Engineer, you will play a key role in designing and delivering intelligent systems that power advanced automation, knowledge retrieval, code generation, and decision-support capabilities. This position offers significant ownership and influence over technical direction, architecture decisions, and the development of scalable AI solutions.

You will collaborate closely with engineering, product, and platform teams to create AI-driven experiences that solve complex business and technical challenges. The level and scope of responsibility will be aligned to experience, with opportunities for substantial impact at every level.

Key Responsibilities

AI Agent Architecture & Optimization

• Design, develop, and enhance multi-step AI agents capable of reasoning, planning, and executing complex workflows.
• Define strategies for context management, task decomposition, error handling, and response quality.
• Establish evaluation frameworks and performance benchmarks to continuously improve agent effectiveness.
• Drive experimentation and innovation across emerging AI technologies and methodologies.

Knowledge Retrieval & Information Systems

• Design and maintain retrieval-augmented generation (RAG) pipelines and supporting infrastructure.
• Develop solutions leveraging vector search, knowledge graphs, semantic search, and related technologies.
• Create knowledge representations that enable accurate reasoning across structured and unstructured enterprise data.
• Improve information retrieval quality, relevance, and scalability.

AI-Powered Code Generation & Data Processing

• Build and optimize systems that convert natural language requests into reliable technical outputs.
• Develop prompt engineering strategies, model selection approaches, and evaluation methodologies.
• Implement safeguards, validation mechanisms, and quality controls for AI-generated outputs.
• Support intelligent automation across data transformation, analytics, and engineering workflows.

Production-Scale AI Systems

• Deploy, monitor, and optimize AI solutions operating in large-scale production environments.
• Improve latency, throughput, reliability, observability, and operational efficiency.
• Evaluate tradeoffs between model optimization, infrastructure improvements, and system architecture changes.
• Contribute to best practices for AI governance, monitoring, and lifecycle management.

Qualifications

What We’re Looking For

• Proven experience developing and supporting AI/ML systems in production environments.
• Strong understanding of evaluation methodologies, performance measurement, and failure analysis.
• Demonstrated ability to make architectural decisions in ambiguous or rapidly evolving technical environments.
• Passion for learning new technologies and adapting to emerging industry trends.
• Strong communication skills with the ability to influence technical direction and participate in engineering design discussions.
• Experience balancing rapid execution with long-term system scalability and maintainability.

Experience

• Approximately 4+ years of professional software engineering experience with meaningful exposure to machine learning, artificial intelligence, or related technologies.
• Candidates ranging from experienced individual contributors to senior technical leaders are encouraged to apply.

Preferred Technical Background

Core Technologies

• Strong programming skills in Python.
• Hands-on experience with large language models (LLMs), generative AI applications, and agent-based systems.
• Experience building retrieval systems using vector databases, semantic search technologies, and/or knowledge graphs.
• Familiarity with cloud-native architectures and distributed systems.

Nice-to-Have Experience

• Knowledge of Kubernetes and modern cloud platforms.
• Experience with Scala, Go, or other systems-level languages.
• Experience working with modern analytics and data processing platforms.
• Exposure to technologies such as Apache Spark, cloud data warehouses, data lakes, and distributed computing frameworks.
• Background in data engineering, business intelligence, analytics, or large-scale data processing environments.

Why Join Us?

• Opportunity to work on cutting-edge AI and machine learning challenges.
• Meaningful ownership and influence over technical direction and product innovation.
• Collaborative environment with highly talented engineers and technical leaders.
• Professional growth opportunities and support for continued learning.
• Competitive compensation package, equity opportunities, and comprehensive benefits.
• Flexible work arrangements and a culture that values impact, innovation, and execution.

Equal Opportunity Employer

We are committed to creating a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other protected characteristic under applicable law.

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AI ENGINEER / ML ENGINEER – APPLIED AI & LLM SYSTEMS

$150,000 – $190,000 BASE SALARY

REMOTE / HYBRID (U.S.)

THE COMPANY

A high-growth technology company building AI-powered solutions to automate complex healthcare data workflows at scale.

• Focused on unstructured clinical and healthcare data transformation
• AI is core to the company’s product and long-term strategy
• Engineering-first culture with strong technical leadership
• Works with large-scale, real-world datasets in regulated environments
• Emphasis on production systems, not experimentation-only AI

THE ROLE

As an AI Engineer / ML Engineer, you’ll design, build, and scale production-grade AI systems focused on document processing, NLP, and LLM-powered workflows.

A deeply technical, hands-on engineering role with high ownership across the full AI lifecycle.

• Build and deploy scalable AI/ML systems using Python and PySpark
• Develop LLM and NLP pipelines for document extraction, structuring, and summarization
• Design and optimize batch pipelines and orchestration workflows (Airflow, Databricks, etc.)
• Productionize AI systems in collaboration with data and platform engineering teams
• Improve performance, latency, reliability, and observability of AI services
• Create evaluation and validation frameworks for model and system quality
• Work with large-scale structured and unstructured datasets
• Contribute to architecture decisions across AI infrastructure and model serving

YOUR SKILLS AND EXPERIENCE

4-10+ years of experience in AI Engineering, ML Engineering, MLOps, or Applied AI

Core Expertise:

• Building and deploying production AI/ML systems
• LLMs, NLP pipelines, or RAG-based systems
• Large-scale data processing and distributed computing

Technical Skills:

• Strong Python engineering background
• PySpark, Spark, Databricks, or similar distributed data tools
• Airflow or equivalent orchestration frameworks
• SQL and data pipeline development
• Experience with AWS, GCP, or Azure
• Monitoring, observability, and system optimization

Additional:

• Experience working with messy, real-world data environments
• Strong problem-solving and systems-thinking mindset
• Ability to own systems end-to-end from design to production

NICE TO HAVE

• Healthcare, clinical, or life sciences experience
• Familiarity with EHR/EMR, claims, or regulated datasets
• Experience with OCR, document parsing, or text extraction pipelines
• Exposure to MLflow, SageMaker, Vertex AI, or model serving frameworks

THE BENEFITS

• $150K – $190K base salary
• Flexible remote / hybrid work options
• High-impact role working on core AI systems
• Strong engineering culture with modern tooling
• Opportunity to shape architecture and technical direction
• Clear growth into senior and staff-level engineering roles

WHY THIS ROLE

This isn’t a research-only or prototype-heavy role-you’ll build AI systems that operate in production at scale.

You’ll work on meaningful, real-world problems where AI directly drives product value, with the opportunity to influence architecture, tooling, and long-term technical strategy.

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Title: AI Engineer

Location: Remote, United States

Compensation: Up to $250,000 + Equity

We’re partnered with a mission-driven healthcare technology company working at the intersection of clinical data and AI. They’re reimagining how complex clinical workflows are automated, with a focus on making high-quality healthcare data more accessible, structured, and actionable. This is a company building something genuinely novel in a space where the stakes are high and the impact is real.

This is a high-impact role where you will lead AI innovation from the ground up. You won’t just be implementing models, you’ll own the full lifecycle of production AI systems, define how clinical data is extracted and structured at scale, and influence the company’s long-term AI direction. The work spans LLMs, computer vision, and mixed-modal approaches in a domain where rigor and accuracy are non-negotiable.

What You’ll Do

• Design, develop, and deploy novel AI/ML systems – with a focus on LLMs and computer vision – to recover, extract, and automate clinical data tasks across diverse data types including medical records, imaging, and clinical reports
• Build robust prototypes and transition them to scalable, near-production-ready code, applying strong software engineering fundamentals throughout
• Design and execute rigorous statistical validation and evaluation frameworks, defining performance metrics and ensuring models meet stakeholder-defined accuracy thresholds
• Own the human-in-the-loop (HITL) lifecycle, ensuring deployed models can continuously improve over time through structured feedback capture
• Partner closely with software engineering to bring proof-of-concept solutions into production, contributing to key architectural decisions along the way
• Proactively identify high-impact AI opportunities across the business and define how advanced capabilities can address them
• Champion best practices for documentation, experimentation, and code quality across the model development lifecycle – and potentially mentor others in doing the same
• Actively evaluate state-of-the-art approaches, bringing innovative ideas and methods to the team
• Apply and uphold healthcare data privacy regulations and ethical standards in all AI development work

Requirements

• MSc or PhD in computer science, engineering, applied mathematics, statistics, or a related field; BSc with equivalent demonstrated experience also considered
• 2-5+ years of relevant experience in AI/ML engineering or data science, with increasing scope and responsibility over time
• Deep hands-on Python expertise; polyglot coder comfortable across modern programming languages
• Significant experience with at least one deep learning framework (PyTorch, TensorFlow, etc.) applied to LLMs or computer vision in production contexts
• Proven knowledge of the healthcare data domain in at least one area: EHR/EMR, clinical imaging, clinical workflows, or clinical research
• Extensive experience with modern cloud compute and storage platforms (AWS, Azure, Databricks, Snowflake, etc.)
• Solid understanding of database technologies (SQL, NoSQL, etc.)
• Strong familiarity with SDLC and agile methodologies
• Ability to independently architect end-to-end solutions and clearly communicate how they deliver business value
• Excellent written and verbal communication skills – including the ability to present complex technical concepts to non-technical stakeholders

Nice to Have

• Experience with computer vision or multimodal model development
• Background in clinical research, regulated healthcare environments, or medical data pipelines
• Familiarity with EDC systems or clinical trial data infrastructure
• Experience designing or improving HITL feedback systems in production
• Exposure to AI evaluation frameworks or quality assessment tooling

If you’re interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

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Principal Data Scientist
Remote or Hybrid, United States.
Competitive salary plus bonus and benefits

This is a senior-level opportunity to shape the direction of data science and artificial intelligence within a high-impact, product-focused environment. You will operate as a technical leader, driving complex initiatives from concept through delivery while influencing how advanced analytics and AI capabilities are embedded into end-user experiences.

The Company
They are an established organisation investing heavily in data science and AI to enhance their products and deliver meaningful outcomes at scale. Operating at the intersection of technology, data, and user experience, they bring together cross-functional teams to solve complex problems.

The Role
* Lead the design and delivery of high-impact data science and AI solutions aligned to strategic business objectives
* Provide technical leadership across multiple workstreams, ensuring projects are well-scoped, prioritised, and delivered effectively
* Collaborate with product, engineering, and business stakeholders to define problems and translate them into scalable data solutions
* Develop and implement production-grade machine learning and AI systems, including generative AI capabilities
* Communicate insights, recommendations, and technical concepts clearly to a range of stakeholders

Your Skills & Experience
* Strong expertise in data science, machine learning, or artificial intelligence, demonstrated through academic or industry work
* Proven track record of building and deploying production-scale data and AI systems, including experience with generative AI
* Ability to independently define problems, design solutions, and deliver results end-to-end
* Experience providing technical leadership and guiding cross-functional teams
* Strong communication skills, with the ability to influence both technical and non-technical audiences

What They Offer
* Competitive salary with bonus and comprehensive benefits
* Opportunity to lead strategic AI and data initiatives with real business impact
* Collaborative, cross-functional working environment
* Flexibility through remote or hybrid working
* Clear progression opportunities within a growing data and AI function

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Staff Applied AI Engineer | Bay Area (Hybrid) | $200k-$298k base + equity

I’m partnering with a high-growth SaaS company at the cutting edge of AI and compliance on a senior Applied AI Engineer hire.

This is not a typical “build a model and ship it” role.

This is where you define what good AI looks like – owning how systems retrieve, reason, and deliver trustworthy outputs at scale.

You’ll sit at the intersection of research and real-world impact, shaping the intelligence behind core product features.

‘ :

* Improving RAG systems – retrieval quality, chunking, embeddings, hybrid search

* Designing evaluation frameworks (metrics, golden datasets, regression detection)

* Building and tuning ranking + reranking systems (cross-encoders, LLM rerankers)

* Running experiments to validate what actually improves performance

* Debugging failure modes across retrieval, reasoning, and generation

* Prototyping agent-style workflows over complex, document-heavy data

* Exploring ML approaches beyond GenAI (ranking, classification, probabilistic models)

‘ :

* 8-10+ years in applied ML, data science, or AI research

* Strong experience in information retrieval / search relevance

* Hands-on with RAG systems and retrieval optimization

* Deep understanding of evaluation + experimentation (A/B testing, metrics)

* Python + strong problem-solving / research mindset

* Someone who can explain why systems work (or don’t) – not just build them

:

* You’ve only used LLM APIs without optimizing retrieval or evaluation

* Your experience is purely prompt engineering

* You prefer purely academic research without product impact

* You’re looking for a heavily structured, slow-moving environment

Candidates must be based in the Bay Area and open to a hybrid setup.

If you’re interested in making AI systems measurably better – not just building them, drop me a message or comment below.

Happy to share more details confidentially.

#AIJobs #MachineLearning #RAG #SearchRelevance #LLMs #Hiring #BayAreaJobs #TechJobs

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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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