Senior Production Systems Engineer 18232

Semicon Service Nordic AB

Job Description Our client is embarking on a strategic initiative to modernize and scale its threat detection and threat-hunting capabilities. While an AI-powered solution already exists, the focus is now on transforming a research-oriented implementation into a resilient, enterprise-grade platform capable of operating efficiently in production environments. This position is ideal for a highly skilled software engineer who is passionate about building scalable systems, improving software quality, and optimizing AI-driven applications. The successful candidate will play a key role in developing an API-centric architecture, enhancing data processing pipelines, and ensuring efficient execution of AI workloads on specialized hardware. The role offers an excellent opportunity to contribute directly to advanced cyber defense initiatives while gaining further exposure to AI/ML operations, large-scale data processing, and GPU-accelerated computing. Key Responsibilities Modernize and refactor existing Python-based AI and machine learning components into maintainable, production-ready software solutions. Develop and optimize large-scale data ingestion, preprocessing, and feature engineering pipelines capable of processing high-volume security-related data streams. Design and implement an API-first architecture to ensure seamless integration with the broader Cyber Defense ecosystem. Facilitate the migration of legacy self-hosted data platforms toward modern cloud-native streaming and processing services. Improve application performance through hardware-aware optimizations, particularly for GPU-enabled environments requiring low-latency threat detection. Establish and maintain comprehensive quality assurance practices, including unit testing, integration testing, regression testing, and CI/CD automation. Collaborate with cross-functional teams to enhance the scalability, reliability, and operational efficiency of AI-driven security solutions. Support the deployment and maintenance of cloud-native infrastructure and containerized applications. Required Experience Extensive professional experience in software engineering with a strong focus on Python-based application development. Proven experience building and maintaining AI/ML support systems and data processing platforms. Hands-on expertise in designing scalable, production-grade software architectures. Experience working with big data ingestion and preprocessing workflows. Exposure to cloud-native environments, containerization technologies, and infrastructure automation. Educational Requirements Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, or a related technical discipline. Required Skills Programming & Software Engineering Python AI/ML Software Development Clean Code Practices Software Architecture Design Testing Frameworks CI/CD Implementation Performance & Systems Engineering GPU Programming CUDA Programming Performance Optimization Low-Latency Systems Design Additional Programming Languages Rust (Preferred) C++ (Preferred) Go (Preferred) Data & Infrastructure Kafka Redis Qdrant Vector Database Data Ingestion Pipelines Data Preprocessing Workflows AI/ML Technologies PyTorch (Torch) Scikit-learn AI/ML Model Support and Deployment Cloud & Containerization Docker Kubernetes Helm Cloud-Native Technologies AWS (Preferred) Google Cloud Platform (Preferred) Domain Knowledge Threat Hunting Security Operations Center (SOC) Cybersecurity Operations Language Requirements Strong professional communication skills in English. Preferred Qualifications Familiarity with cybersecurity environments, threat hunting methodologies, or SOC operations. Understanding of GPU architecture and AI hardware acceleration. Interest in learning and supporting advanced AI models used within cybersecurity applications. Experience working with cloud-based streaming and distributed data processing platforms. Why Join This Project? Contribute directly to strengthening the client's Cyber Defense capabilities and threat detection initiatives. Work on cutting-edge AI and machine learning solutions in a real-world security environment. Gain valuable experience with GPU computing, large-scale data pipelines, and modern cloud-native architectures. Play a pivotal role in transforming innovative AI research into enterprise-grade production systems. Application Method: Interested candidates can apply by sending their profile to hr@semiconservicenordic.com

Hybrus AB

We are looking for a Senior ML Engineer for our client in Stockholm for a long term assignment. Employment type: Fixed Term Contract Duration : 6 Months - 1 Year Location : Stockholm Work type : Onsite ( potential hybrid options) As a Senior ML Engineer, you will be working hands-on to optimise training and deployment of ML models to be quick and cost-efficient. You will also be at the forefront of putting our ML models on mobile devices to enhance data privacy and customer experience. To achieve this, you will need to collaborate with teams to establish best practices and tools for efficient ML model development and deployment, particularly on mobile platforms. You will be expected to help Client reach and stay at the cutting edge of ML training and deployment, as well as explore new frontiers such as federated learning. The impact you will create: ● Lead the technical evaluation and implementation of Federated Learning (FL) initiatives . ● Work closely with Data Science, Android, and Backend teams to design and validate end-to-end FL workflows. ● Define and execute experimentation plans to assess the effectiveness of FL for use cases. ● Develop and optimize language models and on-device training pipelines for privacy-preserving machine learning. ● Establish model evaluation frameworks, success metrics, and validation strategies for FL-based systems. ● Identify technical risks, assumptions, and limitations, and provide recommendations on architecture and future direction. ● Help shape the roadmap for scaling FL from experimentation to production-ready systems What you bring in: ● 5+ years of experience in Machine Learning Engineering, Applied Machine Learning, or related fields. ● Hands-on experience with Federated Learning frameworks such as TensorFlow Federated, Flower, FedML, OpenFL, or equivalent. ● Strong understanding of distributed machine learning, model training, and model evaluation techniques. ● Experience working with NLP, language models, embeddings, or text classification systems. ● Hands-on experience deploying ML models on mobile devices (e.g., TensorFlow Lite, Core ML, ONNX Runtime Mobile). ● Strong knowledge of machine learning frameworks such as TensorFlow and PyTorch. ● Experience designing and executing ML experiments, analyzing results, and driving data-driven decisions. ● Familiarity with privacy-preserving machine learning concepts and challenges. ● Ability to work across multiple teams and communicate complex technical concepts to both technical and non-technical stakeholders. ● Strong problem-solving skills and ability to operate in an exploratory research and PoC environment. It would be great if you also have: ● Experience deploying or operating Federated Learning systems in production environments. ● Hands-on experience with on-device machine learning technologies such as TensorFlow Lite, ONNX Runtime Mobile, or Core ML. ● Experience building machine learning solutions for mobile applications. ● Experience in messaging, spam detection, fraud detection, trust & safety, or similar domains. ● Familiarity with the challenges of running ML workloads on mobile devices. ● Experience with MLOps, model monitoring, and automated training/deployment pipelines. Please let us know if you are interested and if yes, then apply to careers@hybrus.se with your CV, including details about Salary, Notice period and Visa Status.

Celsus Engineering AB

Description Build the next-generation payment platform on a modern and future-proof tech stack. Working in a cross-functional team What we’re looking for Proven ability to design, optimize, and operate data-intensive systems, including schema design, performance tuning, and production troubleshooting in MS SQL Server–based environments. Deep understanding of database performance and reliability, including indexing strategies, query optimisation, and handling production issues. Experience building and operating backend services using .NET/C#, with a solid understanding of microservice architectures and distributed systems. Experience designing and working with asynchronous messaging and event-driven systems, using Kafka, IBM MQ, or similar technologies. Experience running services in containerised and orchestrated environments (Docker, Kubernetes/OpenShift), with awareness of scaling, resilience, and failure modes. Experience contributing to or owning CI/CD pipelines for database changes and deployment automation, with a focus on safe, repeatable releases. A collaborative engineering mindset, with a willingness to share knowledge, learn continuously, and improve how the team builds and runs software. Meritorious with experience from financial services, payments, or other regulated environments. Strong communication skills, with fluency in English; Swedish is a plus