MLOps Jobs in Tallinn.
All active MLOps roles based in Tallinn.
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The ML Platform team at Veriff builds the foundation for rapid, compliant, and reliable iteration on machine learning products. We provide the scalable, observable, and user-friendly systems required to manage data, train models, evaluate performance, and deploy models at scale.
Having already established our core platform capabilities, we are now entering a high-growth phase focused on systemic excellence: institutionalizing world-class observability, optimizing for cost-efficiency, and radicalizing our experimentation speed. Your role will help us bridge the gap between architectural vision and a seamless developer experience for our data science teams.
You’ll help us enable ML innovation by:
- Implementing Observability Frameworks: Building the tools and templates that provide visibility into model performance, data drift, and training statistics, ensuring our continuous retraining loops are robust.
- Engineering for Efficiency: Developing systems to track and optimize compute costs and training performance, allowing us to scale our ML efforts sustainably.
- Building Experimentation Tooling: Executing on the roadmap for internal tools that enable Data Scientists and ML Engineers to iterate and deploy experiments with minimal friction.
- Developing SaaS-grade ML Services: Writing high-quality, maintainable Python code to build and automate services that sit at the core of our ML lifecycle.
- Bridge-Building: Working alongside our Staff Engineer to implement architectural designs and collaborating with SRE/DevXP teams to ensure our solutions are production-ready and easily managed.
You are the right future Veriffian for the job if you have:
- 3+ years of experience in software or ML engineering, specifically building tools that support the ML lifecycle (MLOps).
- Strong Python skills with experience in building internal APIs or automation services.
- Hands-on experience with the open-source ML stack (e.g., MLflow, Kubeflow, Ray, or Prometheus/Grafana for ML monitoring).
- A "Product" mindset for internal tools: You care about the developer experience of the Data Scientists using your platform.
- Experience with SQL and Data Engineering (e.g., Snowflake, Spark, or dbt) to understand how data flows into our training pipelines.
- A skeptical, first-principles approach to engineering—you prefer understanding the "why" behind a system rather than just following a vendor's tutorial.
- Flexibility to work from home
- Stock options that ensure your share in our success
- Extra recharge days on top of your annual vacation
- Comprehensive relocation support to Estonia or Spain
- Extensive medical, dental, and vision insurance to ensure you’re feeling great physically and mentally
- Learning and Development & Health and Sports budget that you are free to tailor to your own needs
- Four weeks of fully paid sabbatical leave after reaching your 5th work anniversary
Ready to apply?
Apply to Veriff
Senior ML Platform Engineer
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We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services
With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.
We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.
Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!
The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms.
We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.
Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations.
Designing, building, and optimising components of Bolt’s ML Platform. Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time. Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance. Proactively solve technical challenges, discover and build new features, enabling develop efficiency. Support our internal users and help with troubleshooting, and turn user problems into scalable solutions. Raise our product and technical quality bar, promoting software engineering best practices.
5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering. Experience in leading and delivering complex cross-team projects. Production experience with Python, Spark, and Kubernetes. Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale. You strive for technical excellence while staying pragmatic to achieve outcomes for the users.
Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!
Accelerate your professional growth with unique career opportunities. Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you. Take care of your physical and mental health with our wellness perks. Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge. Connect with colleagues at annual company events and smaller team gatherings. Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.
#LI-Hybrid
Ready to apply?
Apply to Bolt Technology