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Senior Machine Learning Engineer Computer Vision
Nordic Investin Group
Source: Arbetsformedlingen Platsbanken · original listing ↗
Posted today
About this role
Nordic Investin is recruiting a Senior Machine Learning Engineer Computer Vision on behalf of one of our partner companies. You want technical choices, delivery and production behaviour to reinforce each other, even when the constraints are difficult. The partner is strengthening its capability in production computer-vision systems from labelled data to monitored inference. You will connect PyTorch, computer vision and data pipelines while ensuring that model optimisation and edge inference receive appropriate discipline. The aim is practical progress that colleagues can use, leaders can evaluate and the organisation can sustain. The environment rewards early questions, visible trade-offs and engineering discipline. Security and operability belong in the design. How you will work You will work with product, architecture, security, operations and domain colleagues. The partner values short feedback loops, evidence from real systems and direct communication. This role calls for independent judgement and the ability to raise the quality around you. You are expected to make trade-offs visible, recognise when a decision needs wider expertise and move work forward without creating unnecessary process. What you will do Own the practical direction for production computer-vision systems from labelled data to monitored inference. Translate goals and constraints into a clear approach for PyTorch and computer vision. Establish useful standards, routines or decision artefacts around data pipelines. Coordinate stakeholders and dependencies affecting model optimisation. Use evidence and measurable outcomes to improve edge inference. Strengthen knowledge sharing and sustainable ownership through monitoring. What you will bring Relevant experience delivering production computer-vision systems from labelled data to monitored inference in a demanding environment. Strong working knowledge of PyTorch and computer vision. Practical experience applying data pipelines and model optimisation. Ability to assess priorities, risks and trade-offs involving edge inference. 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 and autonomous systems. Exposure to monitoring in a cross-functional or multi-team 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 labelled data to monitored inference is valuable, while adjacent experience counts when it shows transferable judgement. What makes the opportunity interesting The role offers meaningful ownership and the opportunity to influence both the solution and the decisions around it. The focus on production computer-vision systems from labelled data to monitored inference gives the opportunity a clear mission and room to influence priorities and success measures. 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 ask direct questions and test whether the role, mandate 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 helped improve. Nordic Investin welcomes different routes into the profession and assesses evidence, judgement and potential alongside formal titles.