What if your next ML role started with messy data, cloud constraints, and a system that has to work in production (not just in a notebook)?

At Brillian, that’s often where our work begins. We help companies figure out what’s actually worth building with machine learning, why it matters, and how to make it real in practice.

We’re continuously looking to meet Machine Learning Engineers who enjoy building end-to-end solutions: data → features → models → deployment → monitoring. We don’t always have a matching project starting immediately, but when the fit is right, we’ll stay in close contact and move quickly when something clicks!

What our projects typically look like

You’ll work on greenfield and scaling-phase ML projects that create real business impact. Often, the biggest wins come from getting the data and cloud foundations right, so you’ll be close to those parts too.

Depending on the client and project stage, you might be:

Turning business questions into ML-ready problem definitions and success metrics

Building and improving data pipelines (ingestion, transformation, validation)

Working with modern data platforms to make data usable for modeling and analytics

Designing feature pipelines and training/evaluation workflows that are reproducible

Training, evaluating, and iterating models with clear experiment tracking

Deploying models (batch and/or real-time) and integrating them into products and workflows

Setting up monitoring for data quality, drift, performance, reliability, and cost

Collaborating with engineers and stakeholders to keep delivery grounded in real value

What we value (and what usually works well here)

You don’t need to match a perfect checklist. We care about how you think, how you build, and how you make ML useful in real environments.

Strong engineering instincts and a bias for maintainable solutions

Data realism: you understand pipelines and data quality are part of the ML solution

Production mindset: you care about reliability, monitoring, and running systems over time

Cloud fluency: you can build and troubleshoot in modern cloud environments

Pragmatism: you can say “this shouldn’t be ML” when that’s the right call

Collaboration and clear communication across technical and non-technical teams

And yes, practically speaking, experience in these areas helps a lot:

Python + ML foundations (modeling, evaluation, experimentation, feature thinking)

Data platforms and pipelines (SQL, transformations, orchestration, data quality checks)

Cloud (AWS, GCP, or Azure) and building in cloud-native ways

Shipping ML (APIs or batch jobs, containers, integrations into real systems)

MLOps basics (reproducibility, CI/CD for ML, model registry, monitoring)

Bonus (nice to have): software generalist skills. Many projects include small “make it usable” tasks alongside ML: light UI work, internal tools, dashboards, or wiring outputs into user-facing workflows.

What we offer

High-ownership work where you’ll help shape the solution, not just implement a spec

A team that values clarity and quality (and knows when “simple” beats “fancy”)

Hybrid setup from Helsinki or Tampere, with flexibility to focus when it matters

Salary typically €5,000–€7,000 per month, depending on experience and impact

Opportunity for equity for all new Brillians

What next?

Not sure if you tick every box? That’s okay. We value strong thinking, solid engineering, and the ability to make ML useful in real environments more than buzzword coverage.

Apply via the link below so we can process your application properly. If the timing isn’t perfect right now, we’re still happy to start the conversation and keep in touch.

Please note: we currently hire only within Finland and cannot offer visa sponsorship.

Brillian partners with companies on a joint journey to grow and evolve with digital intelligence — data, software, and intelligent technologies applied across products and operations to drive growth.

We uncover opportunities to create meaningful change, making a genuine difference for businesses, people, and the world.

We don't sell ready answers — we earn them together. Real transformation is built alongside the people who do the work. That’s why we combine industry experience with strategic insight to pursue shared outcomes with integrity.

At Brillian, we believe digital intelligence should be purposeful, responsible, and built to last.

Based in Finland, with teams in Helsinki and Tampere.

Open application - Machine Learning Engineer

Build ML systems end-to-end: data in, model out, monitoring on. Full ownership, real production, the whole chain. Check out more below.