Lead MLOps Engineer

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.
You'll work cross-functionally with data scientists, AI engineers, and product teams to bring the next generation of AI workflows—from fine-tuning to agent orchestration—to life.

• 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 builder's 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 in 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 2–3 weeks. Here's what to expect:

Intro Call – 30 minutes with our team to align on fit and expectationsTechnical Challenge – A practical MLOps design or automation taskTechnical Interview – Deep dive into systems architecture, automation, and ML infrastructureLeadership & Values Interview – Assess alignment with InteractiveAI's culture and growth mindsetOffer – Final conversation and offerWe're building a team of builders — people who care about impact, quality, and growth.
If that's you, let's talk —

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