A hands-on senior ML engineer role in Stockholm, recruited by Nordic Investin on behalf of an unnamed partner company. You build and productionise Python machine learning models — feature, training and inference pipelines, monitoring for drift, latency and cost — and guide technical choices while working with data scientists, platform engineers and product teams.
On behalf of a partner company, Nordic Investin is looking for a Senior Machine Learning Engineer. You are interested in models that perform after deployment, when data shifts, latency appears and users behave differently than the notebook assumed.
The partner is moving machine learning capabilities into core products and workflows. You will develop models and the production systems around them, working with data scientists, platform engineers and product teams.
The partner wants data and AI work that can be operated, explained and improved after launch. Provenance, quality, access and evaluation belong in the solution from the beginning.
How you will work
You will work with engineers, analysts and domain specialists who look at the same information from different angles. The partner expects assumptions, datasets and evaluation methods to be visible. Solutions should be designed for repeatable delivery, monitored use and responsible change after deployment.
As a senior colleague, you will own substantial outcomes and help others make stronger decisions. You are expected to recognise risk early, communicate it without drama and move work forward with practical alternatives. The role still includes hands on delivery; seniority here means broader judgement, not distance from the work.
What you will do
Build and productionise machine learning models in Python.
Design feature, training and inference pipelines.
Evaluate models against product and operational requirements.
Improve monitoring for quality, drift, latency and cost.
Create reproducible experimentation and deployment workflows.
Guide technical choices between classical ML, deep learning and simpler rules.
What you will bring
Strong Python and applied machine learning experience.
Evidence of deployed models used in a real product or process.
Solid software engineering, testing and API development.
Experience with cloud compute, containers and data pipelines.
Understanding of model evaluation and monitoring.
Ability to explain uncertainty and tradeoffs to non specialists.
Experience that would add value
NLP, computer vision or geospatial modelling.
Spark, Databricks or large scale feature processing.
Experience in a regulated decision environment.
A background that can succeed here
Your background may be software engineering, data science, applied research or quantitative analysis. We care that you can connect model performance with production behaviour and user value.
What makes the opportunity interesting
This is a role for someone who wants ownership beyond training a model. The partner offers meaningful data, strong engineering collaboration and the opportunity to shape how machine learning becomes a dependable product capability.
The exact partner, employment model, compensation, start date and working arrangement will be explained openly during the process. Nordic Investin will make sure you understand the context, expectations and decision path before you are asked to commit significant time.
The recruitment conversation
During the process, Nordic Investin will focus on concrete decisions you have made: the context you received, the alternatives you considered, the result you observed and what you would change today. You do not need every optional technology if your core experience transfers and you can explain how you would close the gap.
How to apply
Apply with your CV or LinkedIn profile and a short note describing the most relevant system, product or transformation you have helped deliver. Nordic Investin welcomes candidates with different routes into technology and assesses applicants on relevant capability, judgement and potential.