Lead MLOps Engineer

InteractiveAI; Madrid; Híbrido; EUR 60.000 - 100.000; Jornada completa

Descripción de la vacante

A fast-growing AI startup in Madrid is seeking a Lead MLOps Engineer to design and evolve their ML infrastructure, ensuring best-in-class reliability and scalability. The ideal candidate will have at least 5 years of experience in DevOps or MLOps, strong expertise in Kubernetes and Docker, and a hands-on leadership approach. You will mentor a team while driving CI/CD practices for ML workloads. This role offers a competitive salary along with health benefits and a flexible work setup.

Servicios

Competitive base salary

Performance bonuses

Health & wellness allowances

Flexible work setup

25 days of holidays

Formación

• 5 years of experience in DevOps, MLOps or Infrastructure Engineering roles.
• Experience deploying and maintaining ML workloads in production.
• Strong expertise in Docker and Kubernetes.

Responsabilidades

• Design and evolve ML infrastructure from data ingestion to model serving.
• Build automated end-to-end ML pipelines.
• Drive adoption of CI/CD best practices for ML.

Conocimientos

Containerization expertise

CI/CD pipeline creation

Monitoring tools knowledge

Scripting skills (Python, Bash)

Herramientas

Docker

Kubernetes

Terraform

Prometheus

Descripción del empleo

What You’ll Do

As a Lead MLOps Engineer you’ll own the design and evolution of our ML infrastructure enabling fast, reliable and secure experimentation, deployment and monitoring of AI agents and LLMs in production. You’ll guide a small but high‑impact team of DevOps and ML engineers ensuring our platform achieves best‑in‑class reliability, scalability and velocity.

• Architect and evolve InteractiveAI’s ML infrastructure from data ingestion to model serving and continuous learning loops
• Design and implement scalable, cloud‑agnostic runtimes (Kubernetes / GPU clusters) across on‑prem VPC and hybrid deployments
• Build automation for end‑to‑end ML pipelines (data, fine‑tuning, evaluation, deployment)
• Establish gold standards for reproducibility, observability and model governance
• Partner with AI Engineers to optimize training / inference performance and cost
• Build internal tooling to accelerate AI product delivery and reduce time‑to‑deploy
• Implement robust monitoring, logging and alerting frameworks for ML workloads
• Drive adoption of CI / CD best practices for ML and infrastructure code
• Mentor and grow a small team of MLOps engineers fostering technical excellence and ownership

What We’re Looking For

We’re seeking a hands‑on technical leader who combines deep MLOps expertise with a builders mindset, someone who thrives in fast‑moving environments and can scale both systems and teams.

Minimum Requirements

• 5 years of experience in DevOps, MLOps or Infrastructure Engineering roles
• Proven track record deploying and maintaining ML workloads in production
• Strong expertise in containerization and orchestration (Docker, Kubernetes)
• Experience building CI / CD pipelines for ML models and infrastructure
• Proficiency with infrastructure‑as‑code tools (Terraform, Pulumi, CloudFormation)
• Strong coding / scripting skills (Python, Bash or similar)
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK, etc.)
• Experience with at least one major cloud provider (AWS, GCP or Azure)
• Strong understanding of ML lifecycle management (training, evaluation, deployment, monitoring)

Additional Requirements

• Experience with MLflow, Weights & Biases or other model‑tracking systems
• Understanding of fine‑tuning workflows (LoRA, QLoRA, PEFT) and LLM serving
• Exposure to RAG systems, vector databases and large‑model inference optimization
• Experience implementing security and compliance practices (GDPR, ISO 27001, etc.)
• Prior experience leading technical teams or mentoring engineers
• Familiarity with distributed training and GPU cluster management is a plus

What You’ll Get

• Competitive base salary (from 60,000 / yr to 100,000 / yr) + performance bonuses
• Future equity opportunity for high performers
• Health & wellness allowances
• Private health insurance
• Flexible work setup – travel when needed (ideally Hybrid in Lisbon or Madrid)
• 25 days of holidays / paid time off (excluding local public holidays)

Who You Are

• Proactive & strategic – you anticipate system and organizational needs, designing scalable and future‑proof solutions.
• Technical leader – you raise the bar for engineering excellence and help others do their best work.
• Accountable & high ownership – you take full responsibility for uptime, performance and delivery.
• Builder mentality – you’re comfortable with ambiguity, moving fast while maintaining reliability.
• Collaborative partner – you communicate clearly, build trust across teams and balance pragmatism with long‑term vision.

Interview Process

We keep our process focused and respectful of your time. Most candidates complete it in 23 weeks. Here’s what to expect:

• Intro Call – 30 minutes with our team to align on fit and expectations
• Technical Challenge – a practical MLOps design or automation task
• Technical Interview – deep dive into systems architecture, automation and ML infrastructure
• Leadership & Values Interview – assess alignment with InteractiveAI culture and growth mindset
• Offer – final conversation and offer

About Us

InteractiveAI is a fast‑growing startup on a mission to empower enterprises with fully managed AI agent lifecycles.

We are building the next generation of enterprise‑AI solutions delivering an end‑to‑end Agentic IDE alongside an extensible ecosystem of agentic resources and solutions.

Our platform allows companies to orchestrate, monitor, evaluate, deploy and improve AI agents and soon fine‑tune and own their own models.

We value autonomy, speed and innovation and were building a world‑class team to match. Our squads are lean, focused and execution‑driven.

If you thrive in high‑performance environments and want to be part of a company that rewards transformational outcomes, this is for you.