Senior Machine Learning Operations Engineer

Level: Senior / Lead

Type: Full-time

About the Role

As a Senior/Lead Machine Learning Operations Engineer, you will design and evolve the ML platforms, pipelines, and tooling that power our AI solutions. You'll build the foundation that enables our ML engineers to deliver faster, scale better, and experiment more freely.

From data ingestion to model deployment, your work will make ML delivery more reliable, efficient, and self-service across the organization. You'll partner with applied ML engineers to ensure our infrastructure is not just robust, but also tailored to the unique challenges of large-scale NLP and LLM systems.

What you'll do

• Build and maintain ML platforms, feature stores, dataset versioning systems, and model deployment frameworks.
• Design CI/CD pipelines and automated workflows for ML development and production.
• Improve data processing pipelines for training, evaluation, and inference workloads.
• Create evaluation and monitoring frameworks to ensure ML models perform consistently in production.
• Collaborate with ML engineers to optimize training and inference infrastructure for speed, cost, and scalability.
• Enable self-service ML capabilities for other teams, boosting productivity and enabling scalable growth.
• Stay current with emerging trends in ML infrastructure, LLMOps, and cloud services.

What we're looking for

• Strong experience building ML infrastructure at scale, including pipelines, monitoring, and deployment systems.
• Deep understanding of MLOps best practices and tools.
• Proficiency with Python and backend/cloud technologies (Azure preferred).
• Experience with dataset versioning, feature stores, and reproducibility tools.
• Ability to optimize compute resources for training and inference workloads.
• Bonus: Experience with LLMOps — prompt management, evaluation suites, human feedback loops.
• Strong problem-solving skills and the ability to collaborate with globally distributed teams.

Why you'll love this role

You'll be the multiplier for our entire ML team — enabling faster delivery, higher reliability, and more innovation. If you love building the systems that make world-class ML possible at scale, this is where you can have maximum impact.

What it's like working at Sievo

• One of the coolest offices in the heart of Helsinki – or if you prefer, a flexible hybrid working model. We also provide all essential tools to work remotely.
• Freedom and responsibility. We are looking for people who yearn for this freedom, can make the most out of it and are willing to take on the responsibility.
• International team members coming from over 40 nationalities.
• Awesome perks including extensive healthcare, phone plan, home internet connection, equity program, referral bonus, and many more!

We offer relocation support and a comprehensive package for exceptional candidates.

How to apply

Does this sound like your kind of role?

We are saving you a seat! Please send us your CV through our application system. Additionally any GitHub links, contribution to open-source projects, and displays of passions projects are all welcome.

We are continuously reviewing applications on an ongoing basis and offer flexible starting dates.

For any questions, reach out to edwin.samar@sievo.com (Engineering Manager).

Meet Sievo

We are Sievo – a fast-growing software-as-a-service company from Finland. Our unique superpower is called procurement analytics. We are the global leaders in our space and help our customers understand their own procurement data, make data-driven decisions, reduce emissions, drive supply chain resilience, and beyond!  Each year, we process over 2% of the world’s total spend. Pretty cool, right?

At Sievo, we’re powered by smart and kind people from all over the world. Our 400 Sievonians are based in Helsinki, Chicago and Bucharest.

At Sievo, we celebrate and support differences and strive to create a culture where everyone feels valued and included. As an Equal Opportunity Employer, we do not discriminate against any individual in hiring or employment based on gender, gender identity or expression, age, ethnic or national origin, nationality, language, religion or belief, opinion, disability, state of health, sexual orientation, or other personal reasons.