Company Background

Our client is a leading life insurance company, part of a global financial services group. The company offers a wide range of products, including annuities and life insurance, delivered through a large nationwide network of agents.

Project Description

The project focuses on a production system managing clients and life insurance programs. The role involves both support and new feature development, with a strong emphasis on building and optimizing data pipelines and working within a modern Azure-based data platform.

Technologies

• Azure
• Databricks (Architecture, Unity Catalog, Delta, Lineage, Permissions, Databricks Genie, Notebooks)
• Agentic AI (Mosaic AI)
• Python
• SQL

What You'll Do

• Develop and maintain data pipelines within the Azure-based data platform;
• Work with the Databricks ecosystem (Delta Tables, Unity Catalog, notebooks) to process and manage data;
• Build and optimize data transformations using Python and SQL;
• Develop and support AI-driven data pipelines and automation using Databricks (Mosaic AI or similar tools);
• Support and enhance existing production data systems;
• Collaborate with a team of engineers on Databricks-based solutions;
• Ensure data quality, consistency, and reliability across data pipelines;

Job Requirements

• 3+ years of experience as a Data Engineer;
• Strong experience with Databricks ecosystem (Architecture, Unity Catalog, Delta tables, lineage, permissions, Databricks Genie, notebooks);
• Strong experience with Python;
• Solid proficiency in SQL;
• Experience working in Azure cloud environment;
• Experience with Databricks pipelines AI automation (Mosaic AI or AWS Agentcore);

Nice To Have

• Experience with Azure data integration tools (Synapse Pipelines, Azure Data Factory);
• Experience with Azure SQL pools;
• Understanding of performance tuning for data workloads;
• Experience with CI/CD, DevOps practices, Infrastructure as Code (IaC);

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Company Background

Our client is a leading life insurance company, part of a global financial services group. The company offers a wide range of products, including annuities and life insurance, delivered through a large nationwide network of agents.

Project Description

The project focuses on a production system managing clients and life insurance programs. The role involves both support and new feature development, with a strong emphasis on building and optimizing data pipelines and working within a modern Azure-based data platform.

Technologies

• Databricks (architecture, Unity Catalog, Delta Tables, data lineage, permissions, Databricks Genie, notebooks)
• SQL
• Python
• Azure

What You'll Do

• Develop and maintain data pipelines within the Azure-based data platform;
• Work with the Databricks ecosystem (Delta Tables, Unity Catalog, notebooks) to process and manage data;
• Write, optimize, and maintain data transformations using Python and SQL;
• Support and enhance existing production data systems;
• Collaborate with a team of engineers on Databricks-based solutions;
• Ensure data quality, consistency, and reliability across data pipelines;

Job Requirements

• 3+ years of experience as a Data Engineer
• Strong experience with Databricks ecosystem (architecture, Unity Catalog, Delta tables, lineage, permissions)
• Solid knowledge of SQL
• Strong experience with Python
• Experience working in Azure cloud environment
• Good understanding of data pipelines and data platform architecture
• Strong analytical and problem-solving skills
• Excellent communication skills
• English level: B2 (Upper-Intermediate) or higher

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Company Background

Our client is a leading life insurance company, part of a global financial services group. The company offers a wide range of products, including annuities and life insurance, delivered through a large nationwide network of agents.

Project Description

The project focuses on a production system managing clients and life insurance programs. The role involves both support and new feature development, with a strong emphasis on building and optimizing data pipelines and working within a modern Azure-based data platform.

Technologies

• Azure
• Databricks (Architecture, Unity Catalog, Delta, Lineage, Permissions, Databricks Genie, Notebooks)
• Synapse (Pipelines)
• Azure SQL pools
• Python
• SQL
• Performance tuning

What You'll Do

• Develop and maintain data pipelines in the Azure environment;
• Work with Azure SQL Pools for data storage and processing;
• Write and optimize SQL queries;
• Perform performance tuning for queries and data workflows;
• Collaborate with a team of engineers on Databricks-based solutions;
• Build and orchestrate data workflows using Synapse Pipelines / Azure Data Factory;
• Ensure reliability and consistency of data pipelines;

Job Requirements

• 3+ years of experience as a Data Engineer;
• Solid proficiency in SQL;
• Experience working in Azure cloud environment;
• Experience with Azure SQL Pools;
• Strong understanding of performance tuning for data workloads;
• Experience working in Azure cloud environment;
• Excellent communication skills;
• English level: B2 (Upper-Intermediate) or higher;

Nice To Have

• Experience with Azure data integration tools (Synapse Pipelines, Azure Data Factory);
• Experience with Python;
• Experience with Databricks ecosystem (architecture, Unity Catalog, Delta tables, notebooks, lineage, permissions);
• Experience with CI/CD, DevOps practices, Infrastructure as Code (IaC);
• Familiarity with Databricks Asset Bundles;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Company Background

Our client is a leading life insurance company, part of a global financial services group. The company provides a range of financial products, including annuities and life insurance, delivered through a large nationwide network of agents.

Project Description

The project focuses on ensuring quality and reliability of systems within the financial domain, including validation of business-critical workflows and data processing.

Technologies

• Python
• Azure
• SQL
• Databricks
• Automation frameworks

What You'll Do

• Perform manual testing of application features and workflows;
• Develop and maintain automation tests using Python;
• Work with existing automation frameworks and improve test coverage;
• Validate data and perform database checks using SQL;
• Collaborate with development and QA teams to ensure product quality;
• Identify, document, and track defects;

Job Requirements

• 3+ year of experience in QA;
• Experience with Databricks ecosystem;
• Experience working in Azure cloud environment;
• Good understanding of data pipelines and data platform architecture;
• Experience with Python for test automation;
• Understanding of automation frameworks;
• Experience working with SQL;
• Strong knowledge of manual QA practices;
• Attention to detail and analytical mindset;
• Ability to work in a team environment;
• English level: Upper-Intermediate (B2) or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Project Description

We are looking for an experienced Data Engineer with deep expertise in Databricks to join our advanced analytics and data engineering team. The ideal candidate will play a key role in designing, building, and optimizing large-scale data solutions on the Databricks platform, supporting business intelligence, advanced analytics, and machine learning initiatives. You will collaborate with cross-functional teams to deliver robust, scalable, and high-performance data pipelines and architectures.

Technologies

• Databricks (including Spark, Delta Lake, MLflow)
• Python/Scala
• SQL
• ETL concepts
• Distributed data processing
• Data warehousing
• Cloud Platforms & Storage

What You'll Do

• Lead the design, development, and deployment of scalable data pipelines and ETL processes using Databricks (Spark, Delta Lake, MLflow);
• Architect and implement data lakehouse solutions, ensuring data quality, governance, and security;
• Optimize data workflows for performance and cost efficiency on Databricks and cloud platforms (Azure, AWS, or GCP);
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights;
• Mentor and guide junior engineers, promoting best practices in data engineering and Databricks usage;
• Develop and maintain documentation, data models, and technical standards;
• Monitor, troubleshoot, and resolve issues in production data pipelines and environments;
• Stay current with emerging trends and technologies in data engineering and Databricks ecosystem;

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• 5+ years of experience in data engineering, with at least 2 years of hands-on experience with Databricks (including Spark, Delta Lake, and MLflow);
• Strong proficiency in Python and/or Scala for data processing;
• Deep understanding of distributed data processing, data warehousing, and ETL concepts;
• Experience with cloud data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage);
• Solid knowledge of SQL and experience with large-scale relational and NoSQL databases;
• Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for data engineering;
• Experience with data governance, security, and compliance in cloud environments;
• Excellent problem-solving, communication, and leadership skills;
• English: Upper Intermediate level or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Sep 25, 2025 12:50

The Opportunity

As a Staff Data Scientist at PandaDoc, you will serve as a senior analytical leader, embedding yourself deeply in our product and business data to uncover non-obvious insights and drive actionable recommendations. A primary focus of this strategic role is to champion and drive the organizational shift toward a data-driven culture. You will own the advancement of our experimentation capabilities, train other analysts and data scientists on causal methodologies, and leverage your expertise to provide leadership with a clear, reliable understanding of true impact and causality.

You will report to the Director of Product Data and act as a strategic thought partner to Product, Finance, Design, Engineering, Product Marketing, and executive leadership, ensuring alignment between data insights and critical business decisions.

What You'll Do

Experimentation & Causal Strategy

• Lead the Experimentation Roadmap: Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows, churn risk, and long-term value (LTV).
• Advanced Experiment Design: Design, implement, and rigorously analyze complex A/B tests, multivariate experiments, and adaptive experimentation methods, including the application of Bayesian experimentation, to assess the effectiveness of proposed product changes and business levers.
• Causal Inference Beyond A/B: Apply advanced causal inference techniques (e.g., difference-in-differences, synthetic control, propensity score matching, and instrumental variables) to scenarios where randomized controlled trials (RCTs) are infeasible.
• Deep Dive Analysis: Conduct complex, proactive, and exploratory analysis to discover latent user behavior, emerging trends, and root causes of changes in key metrics, translating these findings into actionable product and business insights.
• Develop Measurement Frameworks: Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes, ensuring consistent and scalable measurement across the organization.

Technical Leadership & Influence

• Scaling Data Science: Partner with Data Engineering to design and build scalable, self-serve experimentation tooling and reusable analytical assets and frameworks (e.g., causal machine learning models) that empower other analysts and data consumers.
• Strategic Influence: Act as a strategic thinker by translating complex statistical findings into clear, compelling, and actionable business narratives for cross-functional partners and senior leadership (VP/C-suite), driving strategic decisions and investment priorities.
• Mentorship and Training: Serve as a technical subject matter expert, training and mentoring junior and mid-level data scientists on best practices in statistical rigor, experimental design, and causal modeling.

About You

Qualifications

• Experience: 6+ years of professional experience in an applied data science, economics, or product analytics role, with a proven track record of leveraging experimentation and causal inference methods to drive significant business impact.
• Education: B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline. A Master’s degree in a quantitative field (e.g., Statistics, Data Science, Econometrics, Operations Research) is preferred, but not required.

Required Technical Expertise

• Causal Inference: Demonstrated expertise in applying a wide range of Causal Inference methods, e.g. Quasi-Experimentation, Matching Methods (PSM), Difference-in-Differences, and/or Instrumental Variables.
• Experimentation Methodologies: Expertise in advanced statistical methodologies for A/B testing, including sample size calculations, sequential testing, dealing with interference/network effects, variance reduction techniques (e.g., CUPED), etc.
• Deep Analytical Methods: Mastery of advanced statistical modeling, time-series analysis, and quantitative methods necessary to perform thorough exploratory data analysis, produce timely insights, and provide actionable recommendations.
• Programming: Advanced proficiency in Python or R for statistical modeling, with experience using relevant data science packages (e.g., SciKit-Learn, numpy, pandas).
• Data Tools: Expert-level proficiency in SQL and experience working with established data warehouses (e.g., Snowflake, Postgres).
• Data Pipelining: Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks is a strong plus.

Key Attributes

• Strategic Communication & Influence: Possesses exceptional communication, presentation, and data storytelling skills with a consistent record of influencing cross-functional partners and leadership at all levels, particularly in navigating and driving consensus in unstructured or ambiguous environments.
• Change Management: Proven ability to drive organizational change management in environments where experimentation and data-driven decision-making are not yet widely adopted.
• Thrive in ambiguity: Ability to navigate significant ambiguity, translate complex business questions into clear analytical frameworks, and manage multiple competing priorities in a fast-paced environment.
• Relevant Experience: Experience in a SaaS domain and a strong focus on Product Data Science are strongly preferred.

Company Culture: 

• We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.
• Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers. 
• Check out our LinkedIn to learn more. 

Benefits:

• Our benefits include tremendous career growth opportunities, a competitive salary, health and commuter benefits, company paid life & disability, 20+ PTO days, 401K and FSA plans, and of course, a fun team of Pandas to work with!

PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.

About the Role

As a Lead Software Engineer in our Machine Learning department, you will take ownership of high-impact initiatives that drive product quality, monetization, and user experience. You’ll apply your expertise in Python, data analysis, and modern AI tools to build, deploy, and optimize ML solutions end-to-end. This is a hands-on technical role that blends data science and engineering to deliver measurable business outcomes. You’ll collaborate closely with cross-functional stakeholders and contribute to evolving areas such as LLMs, Generative AI, and ML infrastructure. The role offers exposure to complex data challenges and the opportunity to shape Pearl’s AI-driven capabilities.

What You’ll Do

• Build, train, and deploy ML models that improve product performance and monetization.
• Collaborate with data, product, and engineering teams across multiple internal initiatives.
• Design and implement data pipelines for extraction, transformation, and analysis.
• Apply statistical and machine learning techniques to real-world business problems.
• Work on projects involving LLMs and Generative AI technologies.
• Analyze large datasets to identify trends, insights, and optimization opportunities.
• Integrate ML models into production systems and monitor their performance.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders.
• Experiment with emerging AI tools and methodologies to enhance existing workflows.
• Ensure data quality, reliability, and scalability in all deliverables.

What We’re Looking For

• 3+ years of hands-on experience in ML Engineering or Data Science.
• 5-6+ years total experience in software or data engineering.
• Strong programming skills in Python.
• Proficiency in SQL for data querying and analysis.
• Solid understanding of data processing, analysis, and visualization.
• Experience with LLMs / Generative AI tools (e.g., OpenAI, Copilot, Cursor).
• Ability to build and deploy ML models end-to-end.
• Strong analytical and problem-solving mindset.
• Experience with .NET for integration work 
• Upper-intermediate English proficiency (B2 or higher). 
• Familiarity with Databricks or similar data platforms (nice-to-have).
• Exposure to AWS or other cloud-based ML environments (nice-to-have).

About Shelf

The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.

We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.

Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.

If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.

Our mission is to empower humanity with better answers everywhere.

Senior Frontend React Developer:

As a Frontend Engineer at Shelf, you'll craft the interfaces that make enterprise AI accessible and trustworthy. While others are building chatbots, we're solving the harder problem: how do you build UIs that help users confidently navigate AI-powered systems processing millions of documents, while maintaining enterprise-grade reliability?

You won't just build React components — you'll architect production-ready Next.js applications that handle high-load scenarios with complex states, real-time AI streaming, and multiple layers of enterprise functionality. Every interface decision you make directly impacts how knowledge workers at the biggest companies in the market interact with their most critical information.

This is frontend engineering at its most demanding. You'll tackle challenges like building real-time streaming interfaces for LLM responses, architecting state management for concurrent AI operations across multiple tenants, creating accessible interfaces for complex knowledge graphs with thousands of nodes, and ensuring blazing fast interactions even with petabytes of searchable content. Your components will bridge everything from enterprise authentication systems to cutting-edge AI models, requiring both sophisticated technical skills and sharp product instincts.

We obsess over frontend quality because we're building the trust layer for AI itself. When your interfaces gracefully handle edge cases, provide clear feedback during AI processing, and remain performant under load, you're not just meeting UX standards - you're directly enabling users to trust AI-powered answers and make critical business decisions with confidence.

You'll work on production SSR applications serving thousands of enterprise users, implementing localization for global markets, ensuring accessibility compliance, and maintaining security standards that pass SOC 2 audits. Your code will integrate with our Elasticsearch clusters, DynamoDB tables, and Aurora PostgreSQL databases through the largest park of REST APIs, handling real-time websocket updates for AI streaming and collaborative features.

We're a product company that ships fast without compromising on lasting quality. You'll work alongside proactive, ever-learning engineers who actively use AI coding assistants (OpenAI Codex, Claude Code) to accelerate development. We build custom MCP servers, implement DSPy pipelines for LLM optimization, and experiment with different AI tools for implementation. In our environment, AI isn't just what we build — it's how we build.

The best engineers we know are drawn to problems that matter. If you're excited by the challenge of building interfaces that make the AI revolution actually usable and trustworthy for enterprise users, this role offers the rare combination of technical depth, meaningful impact, and the prestige of solving UX patterns that the industry hasn't figured out yet.

Responsibilities

• Design and implement production-ready Next.js SSR applications with complex state management, handling high-load scenarios and real-time AI interactions at scale
• Build interfaces for AI-powered features including streaming LLM responses, semantic search across millions of documents, interactive knowledge graphs, intelligent content recommendations, and AI agentic builders
• Architect component libraries and maintain our design system in Storybook, ensuring reusability, accessibility, and consistent UX patterns across the platform
• Develop enterprise-grade functionality including multi-language support, accessibility compliance, cross-browser compatibility, and security implementations that meet SOC 2 standards
• Create comprehensive technical specifications and component API designs that clearly communicate interface decisions, performance trade-offs, and accessibility considerations
• Build and optimize data-heavy UIs using React Flow for node-based graphs, Highcharts for analytics visualizations, and custom virtualization for handling large datasets
• Instrument components for performance monitoring, track Core Web Vitals, implement error boundaries, and build automated visual regression tests with Playwright
• Take full ownership of the features you build, monitoring their performance in production, optimizing bundle sizes, and ensuring they scale gracefully as user load grows
• Work with SWR for intelligent data fetching, caching, and revalidation strategies that minimize API calls while keeping UIs responsive and data fresh
• Integrate with backend services via REST APIs, handle websocket connections for real-time updates, and implement optimistic UI patterns for seamless user experiences
• Leverage AI coding assistants to accelerate development while maintaining high code quality, and contribute to building internal AI agents that automate frontend workflows
• Stay current with React ecosystem best practices, Next.js updates, AI UX patterns, and modern frontend architecture—experiment with new approaches and share findings with the team
• Contribute to our engineering standards and practices through thoughtful code reviews, mentor colleagues on frontend best practices, and actively participate in our culture of continuous learning

Requirements

• Over 5 years of professional frontend engineering experience, including more than 3 years specializing in React and modern JavaScript/TypeScript
• Production Next.js experience - you've built and shipped SSR applications at scale, understand app router patterns, server components, and the trade-offs between SSR, SSG, and CSR
• Deep TypeScript expertise - you write type-safe code with generics, utility types, and advanced patterns. 
• Complex state management - hands-on experience architecting state solutions for challenging scenarios: real-time collaboration, optimistic updates, multi-tenant data isolation, and large-scale data synchronization
• Enterprise application development - you've built applications with localization (i18n), accessibility, security best practices, and compliance requirements. You understand the complexity beyond "making it work"
• AI/LLM interface experience - you've built interfaces for AI-powered features: streaming token responses, chat UIs, semantic search, or similar real-time AI interactions
• High-load optimization - proven track record optimizing applications for performance under heavy traffic, large datasets, and concurrent operations. You monitor Core Web Vitals and know how to improve them
• Modern CSS mastery - strong expertise with Tailwind CSS and/or CSS-in-JS solutions. You can implement pixel-perfect designs while maintaining responsive layouts and dark mode support
• Write well-structured, testable code with thoughtful component abstractions and clean APIs. You know when to abstract and when to keep it simple
• Strong problem-solving skills and genuine curiosity - you don't wait for designs to be perfect but proactively identify UX issues and propose solutions. You're never satisfied with "good enough" and constantly refine your craft
• Experience with AI coding assistants (OpenAI Codex, Claude, etc.) and eagerness to push the boundaries of AI-assisted development. Part of this role involves creating AI agents to automate portions of the frontend workflow
• Familiarity with observability and monitoring tools like Datadog, Sentry, or similar platforms for tracking frontend performance and errors in production
• Upper-Intermediate or better English skills for technical communication, documentation, and collaborating with distributed teams
• Present your work effectively both verbally and visually - you can articulate design decisions, create component documentation, and explain technical trade-offs clearly

Be a Plus:

• Experience with React Flow, Highcharts, or other complex data visualization libraries
• Understanding of Node.js/Python/backend fundamentals - you can read backend code and contribute to API design discussions
• Experience with SWR, React Query, or similar data fetching libraries
• Hands-on experience with vector search UIs, RAG interfaces, or semantic search implementations
• Familiarity with MCP (Model Context Protocol), DSPy, or other cutting-edge AI frameworks
• Experience with monorepo tools (Lerna, Turborepo, Nx) and managing shared component libraries
• AWS services knowledge (S3, CloudFront, Lambda) and understanding of serverless architectures
• Built or contributed to design systems or open-source component libraries
• Experience with Playwright, Puppeteer, or Cypress for comprehensive E2E testing
• Experience building AI agent interfaces or agentic AI workflows

What Shelf Offers:

• B2B contract
• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software
• Premier AI development environment: GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, v0, MCP Servers, plus credits for experimenting with emerging AI tools

Why Shelf

• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all – it’s the improvements they see in their business KPIs.
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

Our Values:

Quality - We’re united by our focus on world‑class Quality. Quality in all things – starting with everything that leaves your desk. Everything you touch – every email, report, campaign, and piece of code – should be outstanding. Your work product should blow people away. Having people look at what you’ve done and say, “Wow.” That’s the standard here. Remember that how you do anything is how you do everything. Focus on craftsmanship—your ability to make things better.

Momentum - for us means that you should know that the things you’re responsible for are moving forward. When you look around and see something that’s stalled, get it moving again. We pride ourselves on “ball movement.” When your boss or team leaves you with something, they should return to see measurable progress. Small, continuous movement is our recipe for success. Constantly look for how to make the work around you move forward. We want you to initiate solutions, ideas, and progress. Don’t wait for it to come to you—reach out and create movement. All the time.

Accountability - We expect every team member to feel that they are accountable for more than anyone might normally expect. Each of us should feel real responsibility for things even at the edge of our control. We consistently share and align on expectations, give each other open and respectful feedback, and use those two drivers to ensure that every agreement we make with one another is clear and complete.

Hard Work - We’re here to do something difficult together. We care intensely about the mission and we expect that from our teammates. That care means that we work hard here. Hard work comes with long hours, extra effort…and real opportunity at Shelf. Your passion for creating and sustaining output is a part of our DNA. Support each other, cheer each other on, drive the mission forward. Great teams sustain intense effort together to win.

Learning Agility - We’re innovating in one of the fastest‑moving spaces in history at a time of accelerating global change. That’s incredibly exciting and requires each of us to commit fully to learning each and every day so that we can be the best at what we do. None of us know everything. All of us can learn anything. Staying open and constantly curious is a key success driver at Shelf. It also requires humility. We prize people who are consistently humble and open to making mistakes and growing from them. Recognize also that learning itself is a skill…we need you to be really good at it. Keep dialing in your own understanding about how you learn best and push yourself to keep growing.

Adapt and Thrive - Overcoming challenges lives deep in our DNA. We have a proud history of understanding and living the reality that obstacles are our opportunities…they’re the key to our success. Change is a constant in our business and fighting change is counterproductive. We need you to be good at being uncomfortable and understand that discomfort is the key to growth. Cultivate your own ability to adapt and know that struggling well is something you’ll share with every team you’re on at Shelf. Our company stories are about thriving through real difficulty…together.

Win Together - We win or lose as a team. Always. Everything you do here is connected to the rest of the organization. Part of our shared team environment demands full honesty…real candor and directness with one another. We expect you to constantly be thinking about how to support your teammates and the company, always acting in service to our shared mission and what’s best for the organization as a whole.

About Shelf

The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.

We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.

Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.

If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.

Our mission is to empower humanity with better answers everywhere.

Summary

The R&D department plays a pivotal role in driving Shelf to disrupt the market. We are looking for Machine Learning experts that are able to deliver end to end with a blend of experience: Python engineering, ML engineering, and pragmatic Data science and Machine learning research. You will ship end-to-end features—from problem framing and experimentation to service deployment, and ongoing operations—quickly and with high quality. Your work will power ML- and LLM-driven services used by top enterprises like Amazon, Mayo Clinic, AmFam, and Nespresso.

This role requires strong Python engineering capabilities coupled with a strong ability to deliver robust ML solutions, along with ML research literacy to choose sound methodologies, define metrics, and evaluate different approaches effectively.

You’ll work in an agile environment, move fast, and own what you ship.

Responsibilities

• Own end-to-end delivery: ideate, research, prototype, productionize, and operate ML-powered services with an expectation to iterate and ship frequently
• Stand up robust training/evaluation pipelines: dataset curation, labeling/feedback loops, experiment tracking, offline/online metrics, and A/B testing
• Solve problems using sound methodology, evaluate approaches along with 
• Transform ML models and LLM workflows (including RAG) into reusable, versioned, observable production services with CI/CD
• Collaborate with Product Owners to shape our product and requirements
• Conduct and receive code reviews; champion engineering excellence, testing discipline, and documentation
• Leverage AI coding assistants to accelerate development and create internal agents that automate parts of the engineering workflow
• Share learnings through demos, docs, and knowledge sessions; contribute to a culture of continuous improvement

Requirements

• 3+ years of professional experience researching and shipping ML-based solutions, with strong Python skills and a track record of delivering fast without sacrificing quality
• Proven experience in owning research problems end-to-end, starting from initial data analysis, through iterative research phases to delivering on production
• Practical NLP/LLM experience: transformers, embeddings, prompt design, and evaluation; ability to choose and justify metrics and methodologies
• Strong backend fundamentals: designing RESTful services, schema design, data modeling, and performance tuning for SQL and NoSQL stores
• Data processing skills: pandas/NumPy; experience with batch/stream processing and ETL orchestration (e.g., Airflow, Step Functions)
• Strong English verbal and written communication

As a plus

• LLM ops and safety: eval frameworks (e.g., RAGAS), guardrails, red-teaming, prompt optimization at scale
• Model optimization: quantization, distillation, pruning; GPU/accelerator-aware serving
• Experience with AWS ML stack (SageMaker, Batch, Step Functions, Lambda, SQS/SNS, DynamoDB, ECS, EC2, S3)
• Vector databases and search: Pinecone, Elasticsearch, pgvector, FAISS, or DeepLake
• Background in reinforcement learning, agent frameworks, or autonomous agents
• Publications, open-source contributions, GitHub portfolio

What Shelf Offers

• B2B contract
• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software
• Premier AI development environment: GitHub Copilot, Claude Code, OpenAI, TypingMind, v0, MCP Servers, plus credits to experiment with emerging AI tools

Why Shelf

• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all – it’s the improvements they see in their business KPIs.
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

Our Values:

Quality - We’re united by our focus on world‑class Quality. Quality in all things – starting with everything that leaves your desk. Everything you touch – every email, report, campaign, and piece of code – should be outstanding. Your work product should blow people away. Having people look at what you’ve done and say, “Wow.” That’s the standard here. Remember that how you do anything is how you do everything. Focus on craftsmanship—your ability to make things better.

Momentum - for us means that you should know that the things you’re responsible for are moving forward. When you look around and see something that’s stalled, get it moving again. We pride ourselves on “ball movement.” When your boss or team leaves you with something, they should return to see measurable progress. Small, continuous movement is our recipe for success. Constantly look for how to make the work around you move forward. We want you to initiate solutions, ideas, and progress. Don’t wait for it to come to you—reach out and create movement. All the time.

Accountability - We expect every team member to feel that they are accountable for more than anyone might normally expect. Each of us should feel real responsibility for things even at the edge of our control. We consistently share and align on expectations, give each other open and respectful feedback, and use those two drivers to ensure that every agreement we make with one another is clear and complete.

Hard Work - We’re here to do something difficult together. We care intensely about the mission and we expect that from our teammates. That care means that we work hard here. Hard work comes with long hours, extra effort…and real opportunity at Shelf. Your passion for creating and sustaining output is a part of our DNA. Support each other, cheer each other on, drive the mission forward. Great teams sustain intense effort together to win.

Learning Agility - We’re innovating in one of the fastest‑moving spaces in history at a time of accelerating global change. That’s incredibly exciting and requires each of us to commit fully to learning each and every day so that we can be the best at what we do. None of us know everything. All of us can learn anything. Staying open and constantly curious is a key success driver at Shelf. It also requires humility. We prize people who are consistently humble and open to making mistakes and growing from them. Recognize also that learning itself is a skill…we need you to be really good at it. Keep dialing in your own understanding about how you learn best and push yourself to keep growing.

Adapt and Thrive - Overcoming challenges lives deep in our DNA. We have a proud history of understanding and living the reality that obstacles are our opportunities…they’re the key to our success. Change is a constant in our business and fighting change is counterproductive. We need you to be good at being uncomfortable and understand that discomfort is the key to growth. Cultivate your own ability to adapt and know that struggling well is something you’ll share with every team you’re on at Shelf. Our company stories are about thriving through real difficulty…together.

Win Together - We win or lose as a team. Always. Everything you do here is connected to the rest of the organization. Part of our shared team environment demands full honesty…real candor and directness with one another. We expect you to constantly be thinking about how to support your teammates and the company, always acting in service to our shared mission and what’s best for the organization as a whole.