Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Contributing to the design, development, and operation of production ML systems that power AI-driven procurement intelligence products with an accent on transforming large, complex procurement datasets into reliable, user-facing features. Focus on building scalable ML pipelines and services, ensuring they are production-ready, observable, and continuously improving over time.

Location: Helsinki, Finland. Flexible hybrid working model available.

Salary: 6,200–7,800 EUR (higher compensation possible for senior profiles).

Company

hirify.global is a fast-growing software-as-a-service company from Finland that specializes in procurement analytics.

What you will do

• Contribute to the design and implementation of production ML systems, from data preparation and training to inference and retraining workflows.
• Build and maintain Python-based ML pipelines with a strong emphasis on clean structure, testability, and operational reliability.
• Collaborate with product and engineering teams to integrate ML capabilities into real user-facing features.
• Participate in defining and improving model evaluation, monitoring, and retraining strategies.
• Review, refactor, and improve existing ML codebases to raise overall engineering quality.

Requirements

• Strong professional experience building production ML systems in Python.
• Excellent command of idiomatic Python, including modular and maintainable code structure and performance‑aware data processing.
• Experience across the ML lifecycle, such as training, validation and inference pipelines, and feature engineering.
• Ability to contribute to readable, testable, and maintainable ML codebases.
• Experience working with recurring or long-running ML workflows in a production environment.
• Strong communication skills, with the ability to influence technical direction across teams.

Nice to have

• Experience with NLP or text-based classification.
• Familiarity with MLflow or similar tooling.
• Exposure to human-in-the-loop or data labeling workflows.
• Cloud-based ML workloads and cost-aware design.
• Experience collaborating in polyglot environments (e.g. Python + .NET).

Culture & Benefits

• Flexible hybrid working model and essential tools to work remotely.
• International team members coming from over 40 nationalities.
• Extensive healthcare, phone plan, home internet connection, and equity program.
• Freedom and responsibility to drive technical decisions and make measurable business impact.

Hiring process

• Submit your CV through the application system.
• GitHub links, contributions to open-source projects, and displays of passion projects are welcome.
• Applications are reviewed on an ongoing basis, and flexible starting dates are offered.