
QLSE by Qgroup AB · Helsingborg
We're looking for an ML Research Engineer to join Klang AI, a fast-growing product company developing advanced AI solutions within speech and language technolog...
We're looking for an ML Research Engineer to join Klang AI, a fast-growing product company developing advanced AI solutions within
speech and language technology.
Klang AI develops advanced AI solutions designed for organisations where security, privacy and trust are essential. In many
environments, it's not enough for AI to be powerful—it also needs to be transparent, reliable and built with data protection and
compliance at its core.
That's why Klang AI's products are trusted by organisations across the public sector, legal industry and research, helping
transform meetings, interviews and client conversations into searchable transcripts, intelligent summaries and actionable
insights. With more than 100,000 users, you'll have the opportunity to solve challenging technical problems while building AI that
people can truly trust.
Who are we looking for?
We're looking for someone who enjoys solving difficult technical problems and is genuinely curious about advancing modern AI. You
thrive in environments with a high degree of ownership, enjoy learning new things and like turning ideas into working systems.
Experience in one or more of the following areas is highly meritorious:
As a person, you're curious, pragmatic and collaborative. You enjoy experimenting, challenging assumptions and continuously
improving both your own work and the technology around you.Vem söker vi?
What does Klang AI offer?
Klang AI is a product company transitioning from startup to scaleup, with a strong R&D culture and a clear focus on innovation.
You'll work alongside highly experienced engineers and researchers in an environment where ideas matter more than hierarchy and
where curiosity, experimentation and technical excellence are highly valued.
Working at Klang AI means tackling advanced challenges within machine learning, generative AI and speech technology. You'll have
significant ownership, short decision-making paths and the opportunity to influence both the technology and the future direction
of the company while building products used by more than 100,000 users.
This is a direct recruitment, where you'll be employed by Klang AI while Qlose manages the recruitment process.
Have we caught your interest?
If you've made it this far, that's usually a good sign. 🌟
Click Apply and attach your CV or LinkedIn profile—we'll take it from there. We review applications continuously, so don't wait
too long.
Questions? Feel free to reach out to Linnea at linnea.neldemo@qlose.io.
We're looking for an ML Research Engineer to join Klang AI, a fast-growing product company developing advanced AI solutions within speech and language technology. Klang AI develops advanced AI solutions designed for organisations where security, privacy and trust are essential. In many environments, it's not enough for AI to be powerful—it also needs to be transparent, reliable and built with data protection and compliance at its core. That's why Klang AI's products are trusted by organisations across the public sector, legal industry and research, helping transform meetings, interviews and client conversations into searchable transcripts, intelligent summaries and actionable insights. With more than 100,000 users, you'll have the opportunity to solve challenging technical problems while building AI that people can truly trust. As an ML Research Engineer, you will: Train, fine-tune and improve machine learning and generative AI models Design and evaluate algorithms, experiments and benchmarking frameworks Work with datasets, data quality and model performance Build scalable systems that bring AI research into production Collaborate closely with the R&D team on technical decisions, research and product development Who are we looking for? We're looking for someone who enjoys solving difficult technical problems and is genuinely curious about advancing modern AI. You thrive in environments with a high degree of ownership, enjoy learning new things and like turning ideas into working systems. We believe you: Have strong Python skills and solid software engineering fundamentals Have a strong understanding of machine learning and modern generative AI Enjoy driving open-ended technical challenges from idea to implementation Can clearly communicate technical reasoning and collaborate well with other engineers Use modern AI tools effectively to accelerate your work Experience in one or more of the following areas is highly meritorious: Large-scale model training and fine-tuning Transformer architectures and modern LLMs Dataset design, evaluation and benchmarking Distributed training and AI infrastructure CUDA, Triton or GPU optimisation Speech recognition, text-to-speech or audio AI Research, scientific publications or meaningful open-source contributions As a person, you're curious, pragmatic and collaborative. You enjoy experimenting, challenging assumptions and continuously improving both your own work and the technology around you.Vem söker vi? What does Klang AI offer? Klang AI is a product company transitioning from startup to scaleup, with a strong R&D culture and a clear focus on innovation. You'll work alongside highly experienced engineers and researchers in an environment where ideas matter more than hierarchy and where curiosity, experimentation and technical excellence are highly valued. Working at Klang AI means tackling advanced challenges within machine learning, generative AI and speech technology. You'll have significant ownership, short decision-making paths and the opportunity to influence both the technology and the future direction of the company while building products used by more than 100,000 users. This is a direct recruitment, where you'll be employed by Klang AI while Qlose manages the recruitment process. Have we caught your interest? If you've made it this far, that's usually a good sign. 🌟 Click Apply and attach your CV or LinkedIn profile—we'll take it from there. We review applications continuously, so don't wait too long. Questions? Feel free to reach out to Linnea at linnea.neldemo@qlose.io.
Jobbeskrivning Sigma Connectivity’s Edge AI initiatives span multiple domains—computer vision, audio intelligence, sensor fusion, and embedded ML—delivering low‑latency, privacy‑preserving intelligence directly on devices across diverse hardware platforms. Projects routinely involve developing and optimizing ML models for tasks such as gesture recognition, defect detection, object tracking, and contextual human‑machine interaction, deployed on edge hardware including Qualcomm, NVIDIA, NXP, and other MCU‑class systems. Work includes quantization, DSP/NPU acceleration, real‑time analytics, and combined cloud–edge pipelines that enhance precision while keeping compute close to the data source. We are looking for a skilled ML Engineer to join our growing team and contribute to the development of advanced edge AI solutions. Your work will include - Model Design and Deployment: On-Device Design, train, and validate ML models for computer vision, sensor fusion, signal processing, and predictive analytics. Develop and optimize ML pipelines for on‑device inference, including quantization, power/performance tuning, and DSP/NPU acceleration. Monitor, test, and optimize the performance of deployed models to ensure accuracy, scalability, and maintainability. Data Processing & Analysis Build data ingestion, preprocessing, and feature‑engineering pipelines for both edge and hybrid (Edge + Cloud) deployments. Extract, process, and analyse large datasets to generate actionable insights and continuously improve model performance. Collaboration Work with cross‑functional teams—architects, embedded developers, PMs, UI/UX, and customers—to develop and integrate ML functionality into real products. Participate in prototyping, PoCs, and contribute to customer dialogues and technical presentations. Participate in technical discussions, document your work, and clearly explain the trade-offs and decisions behind the solutions you present. Stay Current Keep up to date with the latest trends, tools, and technologies in AI/ML to ensure our solutions are cutting-edge. We are looking for - Strong hands‑on experience in Python, ML frameworks such as PyTorch or TensorFlow, and classical CV libraries (OpenCV, scikit‑learn). Ability to build and deploy ML models for Edge or Embedded platforms, preferably with experience on Qualcomm, Nordic, NXP, or similar SoCs. Familiarity with quantization, model compression, benchmarking, and inference profiling on constrained hardware. Experience with data pipelines, including data validation, augmentation, and performance analysis. Understanding of end‑to‑end ML lifecycle, including experimentation, evaluation, and deployment in production environments. Master’s or PhD in ML, Robotics, Autonomous Systems or related fields. 2+ years of hands-on experience developing and deploying ML models in production. Proven experience in one or more of:Computer vision Time‑series or sensor‑data ML LLM‑based or hybrid AI systems Effective communication skills and experience working in cross-functional teams. Passionate about staying up to date with emerging technologies, methodologies, and industry trends in AI/ML. Bonus: Knowledge of MLOps, FastAPI, Docker, CI/CD, and cloud platforms such as Azure or AWS We Provide - Cutting-Edge Projects: Opportunity to work with industry-defining technologies in terms of applied research and pushing functional boundaries. Vibrant Work Environment: We have technical experts from 25 nationalities as part of our team and disruptive ideas are a daily occurrence whether it is a groundbreaking mesh technology, a radical approach to manage power and performance on edge devices, or creative solutions to enhance model efficiency. Work-Life Balance: We understand the importance of balancing work and personal life. Our flexible work hours and remote work options help you maintain this balance. Competitive Pay: We offer a salary that aligns with industry standards, ensuring you are fairly compensated for your skills and experience. Generous Vacation Time: Enjoy a healthy work-life balance with 25 days of annual paid vacation. We believe time off is crucial for your well-being and productivity. Health and Wellness Benefits: Dedicated yearly health and wellness allocation.
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.