Factorial is building a world-class data and AI platform to help teams make smarter decisions, automate complex workflows, and deliver more value to our customers.
As a Staff ML Engineer, you'll set the technical direction for how we design, build, and ship AI-powered systems across Factorial. You'll own our most ambitious AI initiatives end-to-end—LLM applications, agents, and assistants—and make them accurate, reliable, explainable, and production-ready at scale.
You'll be a force multiplier: raising the engineering bar, mentoring other engineers, and partnering with Product, Engineering, Data, Operations, Sales, and Customer Experience to turn the biggest business opportunities into robust AI solutions—balancing speed, impact, correctness, and long-term maintainability.
You'll be part of the Data Ops – ML & AI team, working within a fast-growing Engineering and Data organization that builds high-impact systems across Factorial.
You will identify, design, build, and deploy AI solutions across the full lifecycle: from problem framing and prototyping to development, productionization, evaluation, monitoring, and continuous improvement—and you'll define the patterns and standards the rest of the team builds on.
A key part of the role is supporting our Data Scientists and Analytics team across the ML lifecycle—helping them take models and experiments from notebook to production, providing the tooling, pipelines, and best practices they need, and acting as the technical partner who turns their work into reliable, maintainable systems.
You'll spend most of your time building with LLMs and modern AI frameworks—designing RAG pipelines, tool-using agents, and assistants with LangChain and the surrounding ecosystem. You'll be expected to understand when an LLM-based approach is the right tool—and when a simpler, more deterministic solution is better.
You'll partner with stakeholders across the company to understand their needs, define success metrics, communicate trade-offs clearly, and ensure the solutions we build are useful, adopted, and measurable.
You'll take ownership of projects from inception to production, working autonomously while leading cross-functional efforts alongside Data Engineers, Software Engineers, Product Managers, and business teams—and you'll help others do the same through technical mentorship and design reviews.
We predominantly use Python, SQL, and modern AI tooling to build, evaluate, and deploy AI solutions. You'll write production-grade Python and work extensively with LangChain and the LLM ecosystem—building RAG systems, agents, orchestration, prompting strategies, and evaluation harnesses.
You'll turn business questions into AI capabilities: defining the right interfaces, retrieval strategies, prompts, tools, and guardrails, and validating them against clear, measurable outcomes.
You'll develop LLM-powered applications and AI products, ensuring they are well-tested, observable, cost-aware, safe, and aligned with business needs.
You'll collaborate with Engineering and Data teams to bring AI systems into production, defining clear interfaces, reliable pipelines, monitoring, and feedback loops—and establishing the architecture and best practices others reuse.
On the ML lifecycle side, you'll act as the engineering backbone for our Data Scientists and Analytics team—pairing with them to productionize their models, building the shared pipelines, frameworks, and monitoring they rely on, and reviewing their work to ensure it's reliable, observable, and maintainable in production.
You'll implement evaluation and monitoring practices to detect quality regressions, hallucinations, latency or cost issues, and changes in user or business behavior.
You'll write documentation, share findings, join and lead technical conversations, and communicate insights clearly to both technical and non-technical stakeholders.
You'll iterate in short development cycles, testing assumptions quickly, learning from results, and improving solutions based on real-world impact.
Read a lot: Get to know Factorial's product, customers, data ecosystem, and current ML & AI initiatives.
Learn a lot: Pair with team members from Data, Product, Engineering, and business teams to understand the main opportunities and challenges where AI can create value.
Analyze a lot: Explore use cases, validate assumptions, prototype quickly, and help define clear success metrics and technical direction for our most impactful AI projects.
Build a lot: Lead and contribute to high-impact AI workflows—LLM applications, agents, retrieval, evaluation, and stakeholder-facing solutions.
Fail a lot: We encourage experimentation. We understand that trying out new ideas, failing, learning, and improving is part of the role.
Talk a lot: Participate in and lead team rituals and stakeholder sessions to ensure what we build solves real business needs and can be adopted effectively.
A degree in Computer Science or a closely related technical field.
5+ years of experience as a Machine Learning Engineer, Software Engineer, or similar role, with a strong track record of taking AI or data-intensive systems to production.
Strong software engineering fundamentals and excellent Python development skills—you write clean, tested, maintainable production code.
Hands-on experience building LLM-powered applications with LangChain (or equivalent frameworks)—RAG, agents, tool use, prompting, and evaluation.
Deep experience across the full lifecycle of AI/ML systems: from problem definition and prototyping to deployment, evaluation, monitoring, and iteration.
Strong analytical skills and the ability to translate ambiguous business questions into structured, measurable problems.
Solid experience with SQL and familiarity with the modern AI/LLM ecosystem.
Experience with production-oriented workflows, including evaluation, testing, monitoring, documentation, and collaboration with Engineering teams.
A demonstrated ability to influence technical direction, set standards, and mentor other engineers.
Excellent stakeholder management skills, with the ability to communicate clearly with both technical and non-technical audiences.
A strong ownership mindset, autonomy, curiosity, and the ability to navigate ambiguity.
Comfortable working in English and with distributed teams.
Willingness to work from our Barcelona office 4 days per week, with 1 day working from home.
Strong plus:
Experience deploying and scaling LLM systems in production (latency, cost, reliability, safety).
Experience with LLMOps and MLOps practices and tools (orchestration, evaluation, observability, vector databases).
Experience with retrieval systems, embeddings, and prompt/agent evaluation.
Experience working in SaaS, B2B products, HRTech, fintech, or business management software.
Experience leading cross-functional initiatives with Product and Engineering teams.
We follow an office-first, flexible approach because we believe the best products are built when people collaborate face-to-face.
For this role, we're looking for someone who can work from our Barcelona office 4 days per week, with 1 day working from home. This helps the team connect, brainstorm, align with stakeholders, and ship together, while keeping flexibility for deep work and personal balance.
We care about people and we also offer a lot of benefits for employees:
High growth, multicultural and friendly environment
Continuous training and learning based on your needs
Alan private health insurance
Healthy life with Wellhub (Gyms, pools, outdoor classes)
Save expenses with Cobee
Language classes with Preply
Get the most out of your salary with Payflow
And when at the office...
Breakfast in the office and organic fruit
Nora and other discounts
Pet Friendly
Diversity is part of our culture, we have more than 43 nationalities in our teams and we are infused in an inclusive environment for all employees and candidates. Please feel free to apply with the way it suits you better! (blind resume, identity pronouns, cover letter, etc). We do not discriminate on any aspect, in fact; Factorial encourages everyone to join us!
Factorial is an innovative Business Management Software solution designed to streamline company processes for small and medium-sized enterprises. Founded in 2016, our mission is to help companies automate workflows, centralize people data, and make better business decisions. With customers across over 60 countries worldwide, we've built a diverse team that's driving change in the business management tech space. Join us as we continue our rapid growth journey!
We own it: We take responsibility for every project. We make decisions, not excuses.
We learn and teach: We're dedicated to learning something new every day and, above all, sharing it.
We partner: Every decision is a team decision. We trust each other.
We grow fast: We act fast. We believe that the worst mistake is not learning from them.
