Senior Computer Vision Machine Learning Engineer

Nordic Investin is recruiting a Senior Computer Vision Machine Learning Engineer on behalf of one of our partner companies. You want architecture, delivery and production behaviour to agree, and you turn difficult constraints into systems that teams can operate and improve.

The partner is strengthening its capability in production computer-vision systems from training to edge inference. You will take responsibility for work that connects PyTorch, vision transformers and data pipelines, while ensuring that model optimisation and edge deployment receive appropriate discipline. The objective is progress that colleagues can use and leaders can evaluate.

The environment suits someone who tests assumptions early, documents trade-offs and treats operability as part of the design.

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.

This role calls for independent judgement and the ability to raise the quality around you. You will be expected to recognise when a decision needs wider expertise, make trade-offs visible and move work forward without creating unnecessary process.

What you will do

• Own the practical direction for production computer-vision systems from training to edge inference.
• Translate goals and constraints into a clear approach for PyTorch and vision transformers.
• Establish useful standards, routines or artefacts around data pipelines.
• Coordinate stakeholders and dependencies affecting model optimisation.
• Use evidence and measurable outcomes to improve edge deployment.
• Strengthen knowledge sharing, decision quality and sustainable ownership across the team.

What you will bring

• Relevant experience delivering production computer-vision systems from training to edge inference in a demanding environment.
• Strong working knowledge of PyTorch and vision transformers.
• Practical experience applying data pipelines and model optimisation.
• Ability to assess risk, priorities and trade-offs involving edge deployment.
• Evidence of clear stakeholder communication and dependable end-to-end ownership.
• Professional English and the judgement to work with sensitive or business-critical information.

Experience that would add value

• Experience from manufacturing, medical technology or autonomous systems.
• Exposure to monitoring in a cross-functional environment.
• Swedish language skills or experience working across Nordic organisations.

A background that can succeed here

Your background may be product engineering, platform work, enterprise technology or consulting. What matters is technical depth connected to user and business consequences. Direct experience of production computer-vision systems from training to edge inference is valuable, while adjacent experience counts when it shows transferable judgement.

What makes the opportunity interesting

The attraction is meaningful ownership in an environment where sound judgement changes both the solution and the decisions around it. The focus on production computer-vision systems from training to edge inference gives the role a clear mission and room to influence priorities and measures of success.

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 opportunity before asking you to make a decision.

The recruitment conversation

Nordic Investin will focus on decisions you have made: the context, alternatives, result and what you would change today. You will also have room to test whether the role and partner environment are right for you.

How to apply

Apply with your CV or LinkedIn profile and a short note about a relevant system, platform or technical change you improved. Nordic Investin welcomes different routes into the profession and assesses evidence, judgement and potential alongside titles.