Jobs at Constructor

Develop and maintain high-load, real-time personalization services for global e-commerce platforms. Improve shopper experiences and business KPIs through applied machine learning, user interaction modeling, personalization and recommender systems, hypothesis validation, and A/B testing. Collaborate with engineering teams and business stakeholders to research, deliver, and communicate personalization capabilities and outcomes.

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.

Own the full enterprise customer journey from kickoff through adoption and ongoing value realization. Build executive and technical stakeholder relationships, lead QBRs and EBRs, translate product performance into business outcomes, manage risks and escalations, provide strategic ecommerce recommendations, maintain success plans, and partner with Account Management on retention and expansion.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

Own enterprise customer relationships from kickoff through adoption and value realization. Lead success planning, QBRs and EBRs, executive stakeholder engagement, escalations, technical-to-business value translation, and proactive ecommerce recommendations. Partner with Account Management on retention and expansion, document customer needs, and improve scalable onboarding and support processes. Fluency in French and experience managing enterprise customers are required.

Lead Constructor's end-to-end security program: manage compliance (SOC 2, ISO 27001), incident response, risk and access governance, vendor security, DLP, AI governance, security exercises, and customer-facing security communications while partnering with platform engineering on cloud and container security.

Lead product analytics by defining metrics, building metric frameworks, analyzing funnels and user behavior, designing and analyzing A/B tests, setting up instrumentation and dashboards, and partnering with product, engineering, and leadership to turn data into product strategy and measurable business impact.

Design and analyze A/B tests, apply statistics and machine learning to improve search, ranking, personalization and recommendations, analyze large-scale behavioral data, build models and tools, and communicate findings to technical and business stakeholders to drive key business metrics.

Design and build large-scale data pipelines and models, create dashboards and tools, define and validate business metrics, ensure data quality and performance across distributed systems, and partner with analysts, engineers, and product managers to deliver actionable analytics.

Lead product strategy for Query and Machine Learning & Recall teams to improve candidate retrieval and query understanding. Define roadmap, productionize SOTA models (vector search, embeddings, LLM-assisted parsing), build evaluation frameworks linking retrieval accuracy to revenue, optimize inference latency and costs, and drive measurable lifts in conversion and revenue.

Design the demo and onboarding experiences for Constructor's e-commerce product discovery platform. Own visual strategy, map interactions for AI/LLM features, produce high-fidelity mockups and assets, and ensure designs scale within the company design system to help customers go live faster.

Lead product marketing for Constructor's ecommerce search and discovery platform: define positioning, messaging, launches, competitive intelligence, and build a PMM team. Partner with Product, Sales, Growth, and Content to translate complex features into customer value, enable GTM, and drive pipeline and adoption.

Lead a cross-functional personalization team building production ML systems for search and browse. Own model design, user representations, embeddings, segmentation, offline evaluation, experimentation, and metrics-driven iteration. Hire, mentor, partner with product/engineering, and contribute technically to architecture and implementation to drive measurable retailer KPI improvements.

Analyze and instrument offsite discovery and SEO/GEO performance for ecommerce sites. Build integrations, ETL pipelines, and models to track organic and AI-driven traffic. Create tooling and frameworks for technical site audits, landing page modelling, SEO experiments, and enablement for product and customer teams.

Analyze large-scale user and product data, design and evaluate A/B tests, define and validate product and business metrics, build dashboards and reports, and partner with engineers, data scientists, product, and customers to translate insights into product improvements.

Design, build, deploy, and maintain high-load, real-time ML-based ranking services and a Ranking Platform. Improve performance, feature delivery (feature store), CI/CD, and collaborate with DS, MLEs, and stakeholders.

Build, deliver, and maintain a customer dashboard using TypeScript and React that interacts with Python/FastAPI backend services. Collaborate with cross-functional teams, design APIs, ensure high-scale performance, analyze dashboard metrics using SQL, and contribute product ideas and stakeholder communications.

Own, design, build, and operate distributed, high-load backend services and data pipelines for ML infrastructure. Partner with ML and product teams to deliver self-service, reliable model serving, storage, and deployment components; ensure observability, scalability, and performance while driving technical decisions and continuous improvement.