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We are hiring a senior individual contributor to join our Data Science team. This is a hands-on role for someone who can take ownership of the full solution, from understanding the problem and building the required data pipelines to developing the model, deploying it, and keeping it reliable in production. You should be comfortable working across data, code, infrastructure, and monitoring independently.
The domain is genuinely hard: noisy sensor and telemetry data, weak and delayed labels, enormous scale, and physical systems that fail in complicated ways. We use whatever technique the problem calls for, from classical machine learning and survival analysis to our own patent-pending deep learning architectures and agentic flows already running in production.
The team moves quickly and operates with a startup mentality: high ownership, short decision paths, and a strong bias toward action. When we encounter a difficult problem, we do not stop at we cant. We ask, How can we?
Moving fast does not mean cutting corners. It means combining resourcefulness and practical judgment with scientific rigor, engineering quality, and production reliability.
We also have proprietary methods for validating results against ground truth, so the feedback loop is real: when a solution works, it ships. You will see your work in production and understand its impact on real fleets.

We are looking for a brilliant Data Engineer- an independent, logical thinker who enjoys solving complex problems and building scalable data solutions. You will own and evolve the data foundations that power Product, Finance, Operations, and Business teams. Working closely with diverse stakeholders, Analysts, and R&D teams, you will serve as a technical partner, translating complex business challenges into robust data models, pipelines, and infrastructure. You should be able to translate business and data requirements into scalable data pipelines and data models, integrating multiple internal and external data sources using the most appropriate technologies. Beyond building pipelines, you will improve data quality, modernize existing data assets, automate manual workflows, and help create a clean, reliable, and scalable data ecosystem that supports the company's growth.
Roles and Responsibilities:
Design and build end-to-end data pipelines - From defining source structures and integrating APIs to delivering clean, trusted datasets that enable analytics, reporting, and operational workflows.
Translate business needs into scalable data solutions based on business priorities and the product roadmap, understand technical requirements, and deliver purpose-built pipelines and tools.
Act as the technical partner for Product, Finance, Operations, and R&D teams, translating business needs into scalable data models, pipelines, and internal tools while ensuring reliable, trusted data across the organization.
Write high-quality, maintainable code, while following best practices and leveraging modern data tooling and CI/CD principles.
Drive data quality and reliability - Monitor, validate, troubleshoot, and continuously improve data quality and pipeline reliability across the data platform.

We are looking for a Full-Stack Engineer who brings strong ownership, clear communication, and a practical, can-do mindset. You will join the Commerce squad and build high-impact capabilities across our core commerce and internal platforms, including Admin experiences that power pricing, promotions, product data, and order lifecycle flows, as well as Operations and Customer Support. You will operate in a fast-paced environment with high standards, partnering closely with Product, Design, DevOps, and cross-functional stakeholders to deliver meaningful business outcomes. This is an opportunity to influence technical decisions, own features end-to-end, and build scalable systems that support critical commerce experiences used across the business.
Roles and Responsibilities:
Design and implement scalable microservices with strong API contracts and maintainable architecture
Own features end-to-end: clarify requirements, propose technical designs, break down delivery, coordinate dependencies, ship, monitor, and iterate based on real usage and business impact
Contribute to event-driven commerce architecture: publish and consume events, design resilient workflows, handle retries and idempotency, and ensure data consistency across services
Work within a Scala-based monolith, adapting quickly to unfamiliar technologies and applying pragmatic refactoring practices
Work with MongoDB and other data stores as needed, designing schemas and access patterns that support scale, performance, and long-term maintainability
Work with AWS cloud infrastructure and production systems, including observability, deployments, and operational readiness.

We are looking for a Full-Stack Engineer who brings strong ownership, clear communication, and a practical, can-do mindset. You will join the Commerce squad and build high-impact capabilities across our core commerce and internal platforms, including Admin experiences that power pricing, promotions, product data, and order lifecycle flows, as well as Operations and Customer Support. You will operate in a fast-paced environment with high standards, partnering closely with Product, Design, DevOps, and cross-functional stakeholders to deliver meaningful business outcomes. This is an opportunity to influence technical decisions, own features end-to-end, and build scalable systems that support critical commerce experiences used across the business.
Roles and Responsibilities:
Design and implement scalable microservices with strong API contracts and maintainable architecture
Own features end-to-end: clarify requirements, propose technical designs, break down delivery, coordinate dependencies, ship, monitor, and iterate based on real usage and business impact
Contribute to event-driven commerce architecture: publish and consume events, design resilient workflows, handle retries and idempotency, and ensure data consistency across services
Work within a Scala-based monolith, adapting quickly to unfamiliar technologies and applying pragmatic refactoring practices
Work with MongoDB and other data stores as needed, designing schemas and access patterns that support scale, performance, and long-term maintainability
Work with AWS cloud infrastructure and production systems, including observability, deployments, and operational readiness.

We are looking for a sharp Marketing Analyst to join our Marketing Analytics team and help drive data-driven growth. In this role, you will combine marketing and business expertise with scalable analytical solutions and innovative measurement methodologies. You will collaborate with internal teams and external partners to enhance measurement capabilities, uncover growth opportunities, and support optimized investment decisions. This role is essential to scaling our marketing efforts through deep insights and strategic analysis. If you have previous experience in Paid Search and Affiliate marketing and are passionate about data-driven growth, this might be a good fit for you.
Roles and Responsibilities:
Analyze and measure marketing performance across Paid Search, Affiliate, and additional marketing channels
Evaluate marketing investment efficiency and identify new optimization opportunities
Build analytical frameworks and scalable data solutions for the Growth team
Collaborate with affiliate partners and third-party vendors to evaluate performance, attribution, and partnership effectiveness
Develop AI-driven analytical solutions and measurement capabilities.

We are looking for a Senior Front-End Infrastructure Engineer to help shape the foundation of our digital ecosystem across multiple brands and products. You will build the infrastructure, tooling, and engineering capabilities that enable teams to move faster, release with confidence, and scale effectively. Your work will directly impact developer experience, platform reliability, performance, experimentation capabilities, and the overall success of our digital brands.
This role is focused on solving complex engineering challenges with organization-wide impact. We are looking for a developer with deep technical expertise, a platform mindset, and a strong sense of ownership, someone who understands how engineering decisions drive business outcomes and enjoys building solutions that improve how teams build, test, release, and scale software across the organization. You will partner closely with Engineering, Product, QA, Data, and DevOps teams to help shape the future of our frontend ecosystem.
Roles & Responsibilities:
Build and evolve the frontend infrastructure, shared tooling, reusable components, and engineering foundations that support multiple brands and product teams
Improve frontend performance through modern web architecture patterns, including server-side rendering, caching strategies, and request middleware
Drive initiatives that improve Core Web Vitals, performance, reliability, and user experience at scale
Own and enhance frontend CI/CD pipelines, release processes, and production readiness practices to enable fast, safe, and reliable deployments
Establish monitoring, observability, and incident response practices that improve platform reliability and production visibility
Build solutions for experimentation, feature flagging, and controlled rollouts to improve reliability and support data-driven decision making
Lead cross-functional technical initiatives, partnering with Engineering, Product, QA, Data, and DevOps teams to solve complex platform challenges
Act as a technical owner for strategic frontend infrastructure initiatives, leveraging modern technologies and AI-powered development workflows to drive long-term platform improvements and organizational impact
Provide technical guidance through code reviews, engineering standards, and knowledge sharing across teams.

we are building an AI-powered reverse engineering agent. As a Frontend Engineer, youll build high-signal interfaces for expert users, security researchers working inside complex binaries and large codebases.
This role is about developer tooling and research productivity, not marketing pages. Youll turn complex analysis outputs into interfaces that are fast, precise, and genuinely useful.
What Youll Do
Build UI for reverse engineering and research workflows
Partner with backend and research teams to surface complex insights clearly
Design and implement interfaces for navigating large, messy codebases
Improve performance, usability, and clarity for expert workflows
Own frontend features end-to-end: from spec → implementation → polish.

we are building an AI-powered reverse engineering agent. As a Security Researcher, youll help shape how the system understands real-world binaries, by reversing complex targets, finding where automation breaks, and turning that insight into product capabilities.
This is a hands-on research role with direct product impact: your work will influence accuracy, explainability, and trust in the results we deliver to security teams.
What Youll Do
Reverse engineer complex binaries and large real-world codebases
Analyze malware samples and vulnerability-relevant behavior (as needed)
Identify edge cases and failure modes in decompilers and reversing workflows
Work closely with engineering to translate findings into robust product features
Validate accuracy and explainability of analysis outputs across diverse targets.

Were building an AI-powered reverse engineering agent. This role is about the backend that makes it real: services that process binaries, orchestrate analysis pipelines, and deliver fast, reliable results.
What Youll Do
Build backend services in Python for large-scale binary analysis workflows
Design APIs and asynchronous workers that handle heavy processing reliably
Integrate with decompilers and internal analysis pipelines
Improve performance, correctness, and observability across the system
Take features from idea → production with high ownership.

What you'll be doing
Agent architecture: Design the evolution from today's production single-agent system to a multi-agent one: orchestration, task decomposition, runtime and framework choices, and a migration path that does not break what design partners already rely on.
Agent capability: Own the prompts, context, skills, and tool design that make the agent genuinely good at detection engineering across multiple security platforms, not just plausible-sounding.
Evaluation platform: Build the harnesses, judges, and golden datasets that turn "the agent feels better" into a number, plus the CI gates that keep regressions from shipping.
Reliability and safety: Keep long-running agentic sessions healthy in production, and build the isolation and guardrails required of an agent working inside enterprise security environments.
Production debugging: Work real failures from production traces, and turn each one into an eval case that can never regress silently.
Technical direction: Make the calls on architecture, sequencing, and quality bar and be accountable for the outcome, including raising how AI-natively the whole team builds.
Cross-team partnership: Partner with product and customer-facing teams on what the agent should do, and with platform teams on the data and integrations it depends on.

What you'll be doing
Multi-cloud architecture: Own the design and implementation of our company's multi-cloud architecture across GCP and AWS, including the cross-cloud standards, boundaries, and tradeoffs that keep two providers from becoming twice the complexity.
Infrastructure as code: Build and maintain the entire environment in Terraform, so infrastructure is reviewable, reproducible, and scales without a person in the loop.
Deployment pipelines from scratch: Create the CI/CD foundation that lets a small team ship quickly and safely, with the testing, gating, and rollback paths that make fast releases boring rather than risky.
Kubernetes at data scale: Run and scale the Kubernetes and containerized workloads behind our company's security data processing, where volume, latency, and cost pressure all show up at once.
Security of our own stack: Own identity, access, secrets, network boundaries, and infrastructure hardening to a standard that holds up under customer security review.
Reliability and visibility: Build the logging, monitoring, and alerting layer that tells us something is wrong before a customer does, and make on-call sustainable as the system grows.
Technical direction: Partner directly with the founding engineering team on architectural decisions, and raise the infrastructure and cloud fluency of every engineer who joins after you.

we are looking for a Head of System Engineering.
What will You do?
● Lead, manage, and develop a team of Systems Engineers and Verification & Validation (V&V) Engineers.
● Oversee a full development cycle process of a multidisciplinary system.
● Implement, guide and enhance system engineering and verification methodologies.
● Build and manage multi-project development working plans.
● Control system requirements settings with traceability to MRD.
● Develop and proof a complex, cross-functional system containing Robotic, Mechanical, Electrical, Software, and Algorithm aspects.
● Explore and define solutions and architectures through methodological system engineering tools and know-hows, in a lean fashion.
● Collaborate with the research, engineering, operations, procurement, and NPI teams.
● Coordinate with clients engineering teams and management to ensure efficient implementation and deployment of the product.

What you'll be doing
Drive the detection product domain: Bring deep expertise in SecOps engineering across SIEM, data pipelines, and SOAR, and help the product team define where the product should excel. Develop a strong understanding of the day-to-day work of SecOps engineers and the challenges they face.
Turn expertise into product insight: Conduct deep, hands-on research across real security environments, SecOps engineering practices, data, and tooling. Combine customer feedback with your own experience and the knowledge of the broader team to identify meaningful problems, opportunities, and product directions.
Shape and execute the roadmap: Translate product insights into a focused roadmap aligned with company strategy and customer needs. Partner with the product and engineering teams to prioritize initiatives, make tradeoffs, define outcomes, and drive execution from discovery through delivery.
Turn problems into product direction: Translate ambiguous problems into clear product requirements and actionable plans. Work closely with engineering, design, and security experts to ensure complex technical problems are translated into products that are useful, intuitive, and technically sound.
Shape and evaluate AI agent capabilities: Define what our companys AI agent should be capable of doing as a SecOps engineer, what good looks like, and where it must be trusted or constrained. Develop evaluation frameworks, scenarios, and ground truth to measure and continuously improve agent performance.
Own product quality and outcomes: Maintain a deep understanding of how the product is used in real-world security operations. Validate assumptions, identify gaps, and use customer feedback, product data, and operational experience to continuously improve the product and its direction.

we are looking for a Mechanical Engineer.
Description:
Design, develop, and implement mechanical designs.
Design electromechanical mechanisms.
Provide support to production and ensure compliance with deadlines, quality and cost targets.
Collaborate with cross-functional design teams such as hardware, electronics, and software.
Collaborate with outsourced validation and manufacturing partners to ensure timely supply of systems and devices on spec.
Develop electro-mechanical enclosures and packaging.

Were looking for a Senior Backend Engineer to help build the core systems powering our company- the infrastructure, APIs, data pipelines, and AI-driven engines behind the product.
Youll own major parts of the backend, work closely with Product, AI, and Frontend, and ship features that are scalable, observable, and secure.
What you will do
What Youll Do
● Build scalable, production-grade backend systems that power our companys core product and AI capabilities
● Own features end-to-end: clarify requirements, design architecture, implement, test, ship, monitor, iterate
● Design and build services that support complex workflows (including AI-driven flows)
● Improve system reliability: observability, monitoring, incident readiness, performance tuning, and cost awareness
● Collaborate tightly with Frontend, Product, and AI/ML to deliver fast iterations with high quality.