WhyHireWrong?

Machine Learning Engineer

• Build ML models for real-time disinformation detection
• Deploy and monitor models in production environments
• Manage data pipelines using streaming and batch processing frameworks
• Make architectural decisions on databases, infrastructure, and system design
• Collaborate across engineering, ML, and intelligence teams

Senior Machine Learning Engineer

Data Scientist

• Take ownership of a defined business domain and its algorithmic needs from problem framing through to deployed solution
• Partner with product, business, and AI engineering teams to automate and integrate models into live applications
• Analyze large scale datasets (think: processing billions of behavioral signals daily) and translate findings into actionable recommendations
• Define and evolve the algorithmic roadmap for your area of ownership
• Apply machine learning, statistical, optimization, and GenAI techniques to real business problems
• Write production grade code following engineering best practices
• Build resilient, maintainable algorithmic pipelines that hold up over time

Data Scientist – Machine Learning, GenAI

• Partner with product teams and business leaders to understand and define Agentic AI use cases
• Collaborate with data scientists across global teams to gather feedback on the agent building experience and translate it into framework improvements
• Shape and drive the evolution roadmap for the Agentic AI framework
• Apply GenAI and Agentic AI techniques to solve real business problems
• Build and maintain resilient, production grade algorithmic and agentic pipelines
• Write clean, well structured code following engineering best practices
• Deepen applied knowledge across machine learning, optimization, statistical modeling, and GenAI

Product Data Scientist

Account Executive

• Taking over qualified prospects from the BDR team and running the full sales cycle from discovery to close
• Running consultative conversations where understanding the client's technical and regulatory context matters
• Coordinating with solution consultants to build proposals that address the actual problem, not a generic version of it
• Managing your pipeline accurately and pushing deals forward without losing momentum
• Representing the company at industry events and client meetings when needed

Analytics Engineer

• Design, build, and maintain reliable, tested, and well documented ETL and ELT pipelines and DBT models
• Work with stakeholders across the business to understand data needs and translate them into high quality, reusable data products
• Identify gaps and improvement areas across the data ecosystem and shape the analytics engineering roadmap
• Build and maintain self-service tools and datasets that allow engineers, data scientists, and analysts to get to insights quickly
• Partner with Product Engineering, Data Science, and Analytics teams to enable effective use of the data platform
• Investigate and resolve data related bugs and technical issues in platform tooling and DBT models
• Contribute to and lead cross-team data projects with a focus on reliability, efficiency, and testability

Frontend Engineer

• Solve complex technical problems at the core of the web and React Native clients
• Build and maintain the shared cross-platform design library of reusable components
• Contribute to the ongoing migration of the website to Next.js and the expansion of React Native across the mobile codebase
• Write hybrid first code that works across both web and React Native
• Define and evangelize technical standards across the engineering organisation
• Improve the efficiency of the design to engineering handoff cycle
• Mentor and coach engineers in Barcelona and across the wider team
• Contribute to shaping the technical roadmap and vision for the platform

Senior Software Engineer – React

Ecommerce

• Define KPI frameworks and own data pipelines
• Deliver data-driven insights that steer growth across Europe and Latin America
• Design and maintain end-to-end data pipelines
• Build and own dashboards using at least one professional visualization tool
• Monitor ongoing business performance and surface anomalies
• Identify levers for growth and retention within the local market
• Collaborate with local market teams, product teams, and HQ data teams

International E-Commerce Data Analyst

Sales Representative – IT Consulting

Network Engineer

• Configure and maintain Cisco switches, access points, and wireless controllers
• Monitor LAN/WLAN and respond to alerts before they cause downtime
• Support IT/OT production networks (PROFINET, Modbus/TCP, EtherNet/IP)
• Provide 3rd-level support and take part in network upgrade projects

Network Administrator

• Build and maintain Angular applications used daily by enterprise clients.
• Implement modern state management and reactive patterns with NgRx and RxJS (or Signals).
• Write clean, testable TypeScript following strict type safety and code review standards.
• Work closely with design to translate UI/UX into accessible, consistent components.
• Maintain a shared design system using Storybook and Angular Material (with optional theming).
• Optimize for performance — from bundle sizes and lazy loading to runtime efficiency.
• Ensure conformance with WCAG 2.2 accessibility guidelines.
• Integrate APIs built with REST and GraphQL.
• Contribute to automated tests (Jest, Cypress, Playwright) and CI/CD pipelines.

Angular Developer – Enterprise SPA

Full-stack Engineer

• Lead production-grade healthcare AI systems: scale distributed Python-based agents, own end-to-end delivery with real patients, in a lean team; make care accessible.
• Deploy and refine AI-driven patient communication and triage systems directly with hospitals and clinics.
• Architect and scale agent orchestration systems built on LLMs and agentic frameworks.
• Build and maintain secure healthcare data layers with low-latency voice and video capabilities.
• Scale distributed systems under real clinical load.
• Work in a small team which means you own things end to end, not hand them off.

Principal Software Engineer

Product Designer

• Design AI-native enterprise workflows for healthcare operations
• Architect dashboards and operational intelligence systems used by hospital leadership daily
• Transform dense clinical and operational datasets into intuitive, decision-ready interfaces
• Build UX patterns for AI-generated insights, recommendations, and protocol deviation alerts
• Create human-in-the-loop validation and auditing experiences for healthcare enterprises
• Partner directly with engineers to design technically scalable systems

Senior Product Designer

• Lead the design and discovery phase for GenAI projects: translate business problems into concrete architectures covering model selection, RAG, agents, fine-tuning, and guardrails
• Build complete GenAI solutions end to end, covering data ingestion, retrieval layers, orchestration (LangChain, LlamaIndex, LangGraph), API and backend
• Design RAG pipelines using vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks
• Own prompting strategies, model selection, and fine-tuning approaches including LoRA, QLoRA, and supervised fine-tuning
• Implement safety and governance controls: input/output filters, PII handling, audit logs, human-in-the-loop mechanisms
• Gather technical requirements directly from client stakeholders and produce reliable delivery estimates
• Mentor other data scientists and engineers on GenAI patterns, code quality, and best practices
• Track the GenAI landscape actively and run targeted proof-of-concepts on emerging approaches

Senior Data Scientist, Fullstack

Backend Engineer

• Lead the technical direction for your team
• Own architecture decisions
• Turn messy business requirements into concrete tasks
• Collaborate directly with PMs, QA, mobile developers, and clients
• Build and maintain CI/CD pipelines
• Use AI tools for daily productivity
• Plan sprints and estimate timelines

Tech Lead – PHP

Product Adoption Specialist

• You'll start by shadowing teams: sales, marketing, product to understand how they actually work, where time gets lost, and where a well-built automation would change something concrete.
• Identify that the marketing team spends four hours a week adapting one piece of content for different formats, and build a workflow that reduces it to twenty minutes.
• Run a one-hour session teaching a sales rep how to use AI to research accounts before calls, then follow up two weeks later to check if they're actually using it.
• Troubleshoot why a workflow that worked last month is now producing inconsistent outputs and fix the prompt architecture.
• Evaluate a new tool that just dropped and decide whether it's worth introducing or just noise.
• Write a one-page guide so a team can run a workflow you built without calling you every time.
• Expect resistance from some, enthusiasm from others. Your job is to turn skeptics into regular users not by selling them on AI, but by showing them something that saves them time today.