SkillHuset Sweden AB jobb

Responsibilities: * Develop and deploy end-to-end microservices-based solutions for batch and real-time algorithms, including monitoring, logging, automated testing, and performance testing. * Design, implement, and optimize MLOps pipelines using tools such as Kubeflow, Seldon, MLFlow, Docker, and Kubernetes. * Collaborate with Data Scientists to enhance the ML model development process and ensure performance improvements. * Ensure scalability, maintainability, and robustness of deployed machine learning models. * Monitor and troubleshoot ML model performance and infrastructure issues in production (experience with Prometheus and Grafana is valuable). * Support and enhance ML software infrastructure, including CI/CD, data storage, cloud services, security, and system monitoring. * Work with cloud platforms, particularly GCP and Azure, to optimize resource allocation and costs. * Stay up to date with the latest trends and best practices in MLOps. Qualifications: * Bachelor's or Master’s degree in Computer Science, Engineering, or a related field. * 5+ years of experience as a Machine Learning Engineer or in a similar role. * Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn. * Strong understanding of MLOps best practices and tools, including Kubeflow, Seldon, MLFlow, Docker, and Kubernetes. * Experience working with cloud platforms, especially GCP. * Knowledge of data processing, ETL, and feature engineering techniques. * Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. * Excellent communication and interpersonal skills.

We are looking for a Junior Lab Assistant for an on-site consulting assignment with one of our clients in Gothenburg. In this role, you will support daily laboratory operations, assist with routine testing, and help ensure accurate sample handling and documentation. About the Role Your responsibilities will include: Preparing samples, materials, and test setups. Supporting routine laboratory and packaging tests (e.g. torque, MVTR, and mechanical testing). Handling and labeling samples according to procedures. Preparing and maintaining laboratory equipment. Recording test results and entering data into laboratory systems. Following established laboratory procedures and documentation standards. Requirements Junior-level experience in a laboratory or similar environment. Ability to follow instructions and standardized procedures. Strong attention to detail and a structured way of working. Good communication and teamwork skills.

About the role We are looking for a Senior Software Engineer with strong hands-on experience in Python, Azure, CI/CD and modern engineering practices. You will improve developer productivity by building internal tooling, reusable automation and scalable CI/CD solutions while supporting Azure-based data platforms. The role combines software engineering, DevOps and data-platform enablement in a cross-functional environment. This is a hands-on engineering role. We are not looking for a pure platform administrator, architect or research-focused ML engineer. Preferred location: Sweden Requirement: EU citizenship Responsibilities - Develop Python-based automation, tooling and engineering workflows. - Build and maintain GitHub Actions, GitHub Workflows and reusable CI/CD pipelines. - Support Azure-based data platforms, including Databricks and related technologies. - Improve software quality, traceability and engineering processes. - Collaborate with engineering and platform teams to deliver scalable technical solutions. Must-have - Strong Python skills for production-oriented automation and tooling. - Practical hands-on experience with Azure Databricks (approximately SFIA Level 3 or equivalent), ideally including development of notebooks, pipelines/jobs or Spark-based solutions. - Experience with Azure data-platform technologies such as Spark, Kafka, Hadoop, schema enforcement, data quality validation or Power BI. - Hands-on experience with GitHub Actions, GitHub Workflows and reusable workflow design. - Solid Docker experience. - Experience working with CI/CD in Windows and Linux environments. - Ability to work independently while collaborating across teams. - EU citizenship. Meritorious - Data governance and data modelling. - Machine Learning model deployment. - GitHub CLI (gh), REST APIs or GraphQL APIs. - JFrog Artifactory or similar. - Bash and/or PowerShell. - Git LFS. - GitHub Enterprise Server and self-hosted runners. - AI-powered developer tools or agentic engineering workflows.

About the Role We are seeking a Senior Software Engineer with a deep background in Google Cloud Platform (GCP) infrastructure, cloud-native architecture, and AI-augmented engineering. You will be taking over a mature, minimal-technical-debt platform spanning over 30 repositories across core GCP services, alongside shared Multi-Cloud (GCP/Azure) environments covering documentation, guidelines, and routines. In this role, you will be the technical anchor for our GCP environment. You will be responsible for "holding" the current setup—ensuring stability, security, and code quality—while simultaneously creating the vision and architectural roadmap for future platform development. Because we work with a Managed Service Provider (MSP) for development execution, this role requires a strong Technical Design Authority. To scale our governance and streamline code-level oversight, we leverage AI tooling and agentic workflows to assist with automated PR reviews and platform context. You will dictate the architecture to the outsourced team while utilizing and evolving these AI capabilities to maintain our high standards efficiently. Core Responsibilities Platform Vision & Strategy: Own the technical roadmap for the GCP platform. Design and architect future capabilities, ensuring the platform evolves using modern, cloud-native best practices. Technical Gatekeeping & Code Review: Act as the final approver for all code merged across the platform by the MSP. Enforce strict internal standards for TypeScript and Python microservices. AI-Augmented Governance: Utilize and tune internal AI harnesses and agentic workflows to automate PR reviews, manage repository context, and enforce platform standards. Architectural Direction (TDA): Translate business needs into highly detailed architectural designs and technical Jira stories, providing exact technical direction for the MSP to execute. Infrastructure as Code (IaC): Maintain and evolve our Terraform modules, managing the lifecycle of GCP projects, networking, and firewall policies. CI/CD & Ecosystem Management: Oversee GitHub Actions workflows, custom NPM packages, and event-driven orchestration (Cloud Run, Cloud Functions, EventArc). Required Technical Skills Google Cloud Platform (GCP): Expert-level knowledge of GCP core services, IAM, networking, security policies, and serverless compute. Software Engineering: Deep proficiency in TypeScript and Python. You must be highly capable of reading, writing, and reviewing complex application logic. AI & Agentic Engineering: Practical knowledge of agentic coding and AI-assisted engineering. You should understand how to leverage, prompt, and maintain AI tools that interact autonomously with codebases. Infrastructure as Code: Extensive, hands-on experience with Terraform (module design, state management, and enterprise deployments). CI/CD & Automation: Strong experience with GitHub Actions and automated quality/security gates. Multi-Cloud Awareness: While this role is heavily GCP-focused, a working knowledge of Microsoft Azure is highly advantageous to align our multi-cloud strategies and shared repositories. The Ideal Candidate Profile You are a Senior Software Engineer who transitioned into Cloud Architecture and Infrastructure, and you embrace the shift toward AI-augmented development. You understand that "Infrastructure is Code" and you treat Terraform with the same rigor as an application backend. You are comfortable being the sole technical visionary for a platform, utilizing AI to enforce strict quality gates, and dictating architectural patterns to an external development team.

Assignment description Design Painter.  Description of the assignment Responsible for the preparation, mixing, and development of high-quality paint finishes across concept models, prototype vehicles, and design surfaces. Works closely with designers, modellers, and Colour & Materials teams to ensure physical design models accurately represent intended colours, finishes, and visual effects, and to influence and refine design decisions through expert finish execution. This role requires advanced craftsmanship, deep technical expertise in automotive paint systems, and a strong ability to solve complex finishing challenges. It also involves setting quality standards, guiding best practice within the team, and contributing to the development of future vehicle design through high-level finish evaluation and delivery. Qualifications and skills required for the role - Extensive experience in paint application and surface finishing within automotive, design studio, prototype, or high-end bespoke environments, delivering premium-quality results. - Proven ability to prepare and finish surfaces to the highest presentation standards, consistently meeting or exceeding expectations. - Advanced experience in mixing, matching, and formulating complex colours and finishes, resolving challenging material issues. - Experience managing paint equipment and materials, ensuring effective maintenance, quality control, and efficient use of consumables. 

Assignment description Our client is seeking a Lead Data Engineer Strong consultant that can take the role as first Lead Data Engineer within BI/DWH modernization project. Must be able to pre-form early in the project and contribute both in discovery/analysis and in the first implementation. Important that consultant is not only a developer but have strong competence to understand complex data warehouse, analyze dependencies and contribute and form the modernization of the legacy flow. Most important is the combination of SQL Server/SSIS-legacy, datamodellering and practical modernisation towards Fabric/Databricks/Snowflake/Azure.  Required Experience Senior Data Engineer  Very strong SQL-competens, especially SQL Server and T-SQL Documented experience of SSIS och traditional Microsoft DWH-/BI-environments Experience of analysing ETL-flows, stored procedures, views, tables and dependencies Experience of modernization or migration from legacy DWH cloud-based data platform Experience of at least one of: Microsoft Fabric, Azure Synapse, Databricks or Snowflake  Good understanding of Kimball, Data Vault, star schema and data marts Experience of CI/CD, Git and structured development flows Used to document technical solutions, data flows, mappings and designer decisions Ability to work close to Architect, BI Developer, Business experts and other Data Engineers. Contribute both in analyse/discovery and hands-on implementation Lead more junior Data Engineers  Meritorious - Experience of: Dbt, SSAS/SSRS/Power BI, Purview, Unity Catalog, DataHub, experience from retail, supply chain, finance, HR or similar domains

Assignment description We are looking for a Data Scientist for our customer. Job description: We're looking for a highly skilled Data Scientist with experience in Linear Programming or Mixed Integer programming and a robust background in analytics. In this role, you will be instrumental in developing, maintaining, and scaling production-grade optimization models. The ideal candidate has a strong background in discrete optimization methodologies, statistics, and machine learning, with the ability to handle everything from complex data wrangling to presenting clear results to our stakeholders. Requires solid Python programming skills -writing clean, efficient, modular, and production-ready code that is easy to maintain and test. Requires strong SQL skills for data manipulation and analysis, ideally experience in DBT / GCP BigQuery is good to have. Optional to have hands-on experience with MLOps and CI/CD pipelines, ideally on Google Cloud Platform. Responsibilities •Maintain and enhance the existing optimization model by proactively identifying shortcomings and implementing improvements. •Present model outputs and analytical findings to stakeholders, gather and translate business requirements into technical solutions, and maintain clear, consistent communication with all stakeholders throughout the project lifecycle. •Ensure the robustness and efficiency of the deployed AI product on GCP through continuous monitoring and maintenance. •Improve the data preparation and wrangling pipeline, and integrate additional data sources to enrich model inputs. •Collaborate with Data Scientists, ML Engineers, and Product Managers to improve the performance, reliability, and scalability of the optimization model. •Implement MLOps best practices for seamless deployment, monitoring, and lifecycle management of machine learning models. •Conduct ad hoc data analyses and develop visualizations to support data driven decision making across teams. Required Skills •Solid knowledge and experience in discrete optimization models (Integer Programming, Mixed Integer Programming) •Proven experience developing and deploying ML models in the cloud, preferably on GCP (beyond notebook-based coding and execution). •Solid Python programming skills—writing clean, efficient, modular, and production-ready code that is easy to maintain and test. •Hands-on experience with MLOps and CI/CD pipelines, ideally on GCP. Strong SQL skills for data manipulation and analysis. •Ability to understand diverse data sources and build robust data wrangling and aggregation pipelines. Familiarity with DBT for data transformation. •Comfortable working in Agile, cross-functional teams. •Strong collaboration skills and ability to thrive in complex, ambiguous problem domains.  Required cloud certification: No