Mlops Engineer
Pubblicato il 22-08-2026 - Soldo in Roma
**Job Information**:
Date Opened
- 28/05/2026 Job Type
- Tempo pieno Industry
- SaaS City
- Roma Country
- Italy Soldo is the proactive spend management solution that frees progressive businesses to accomplish more.
- Over 25,000 organisations across 31 countries use Soldo to end slow, messy, and inefficient spending, bringing financial agility and control over every expense. Soldo frees finance with a uniquely proactive approach to managing decentralised spending.- By combining a powerful spend management platform, a user-friendly app, and versatile payment methods, Soldo automates expense admin to eliminate inefficiency in managing business spending.- By proactively managing decentralised spend, organisations empower employees to spend when and where it's needed, keeping productivity high while avoiding month-end surprises.- Founded in 2015 by Italian digital innovator Carlo Gualandri, Soldo is headquartered in London, with offices in Dublin, Milan, and Rome.- We’re looking for people with big ambitions, cool heads, sharp minds, and warm hearts. Come and join us as we grow together.
**- What's in it for you**
- Competitive salary
- Private healthcare coverage for you and your family
- Lunch Vouchers
- Genuine career development opportunities (we love to see you succeed) - including your own annual €500 career development budget
- Access to training and development - including a mentoring programme, workshops and the opportunity to progress onto our leadership programme
- Flexible working options, including working from home or our Milan or Rome offices + 60 days’ work anywhere
- Statutory Leave entitlements plus extra days off on Christmas Eve,
New Year's Eve and your Birthday
- Your own personal company Soldo card
- Employee Assistance Programme
- CAF Annual Fiscal & Financial Support
**- The role**
- As we continue to scale our AI capabilities, we’re looking for an MLOps Engineer to help us build and operate reliable, production-grade AI systems powering intelligent financial experiences across our platform.- This role sits at the intersection of Machine Learning, Product Engineering and Cloud Infrastructure.- You’ll work closely with AI Scientists, Software Engineers, and Product Managers teams to operationalise ML and GenAI solutions at scale, ensuring performance, reliability, governance and efficiency across the entire AI lifecycle.- This is not a research-oriented Data Scientist role.- We’re looking for an engineer with strong experience building scalable ML infrastructure and deploying AI systems in complex production environments.
**- Responsibilities**
- Design, build and maintain scalable ML and GenAI infrastructure
- Productionise AI models and services across training, deployment and inference workflows
- Build and optimise CI/CD pipelines for ML systems
- Improve reliability, observability and monitoring of AI workloads
- Enable reproducible experimentation,
model versioning and automated deployment processes
- Partner with AI Scientists to accelerate the transition from experimentation to production
- Optimise infrastructure performance, scalability and operational costs
- Support governance, compliance and security best practices for AI systems
- Contribute to the evolution of our AI platform architecture and engineering standards
- Drive operational excellence across the ML lifecycle
**- We’re looking for someone who has**
- Strong experience in MLOps, ML Platform Engineering or AI Infrastructure roles
- Proven experience deploying and operating ML/AI systems in production environments
- Strong Python engineering skills
- Strong knowledge and experience with PySpark and Databricks
- Solid experience with cloud platforms such as AWS, GCP or Azure
- Experience with containerisation and orchestration technologies (Docker, Kubernetes)
- Experience building CI/CD workflows for ML systems
- Familiarity with ML orchestration and experiment management tools such as MLflow, Kubeflow, Airflow or similar
- Experience with monitoring, logging and observability tools
- Understanding of distributed systems and scalable backend architectures
- Experience working in cross-functional SaaS product environments
- Strong communication and collaboration skills
**- It would be nice if you have**
- Experience with LLMOps and GenAI infrastructure
- Familiarity with vector databases and inference optimisation
- Experience in fintech or highly regulated environments
- Infrastructure as Code experience (Terraform or similar)
- Exposure to feature stores and model serving frameworks