Machine Learning Engineer / Data Scientist

IntuiCell AB

This is a career-changing opportunity to work alongside world-class engineers and scientists on a mission to reimagine what machines can do. You will help us build the digital nervous system of intelligent agents, not by refining existing tools, but by inventing new systems entirely. Your work will directly shape how intelligent machines learn, adapt, and act in the physical world. We are now extending our models into robotics, where they act as an adaptive layer between higher-level learning systems, such as reinforcement learning (RL) and vision-language-action (VLA) models, and low-level actuators. This layer can significantly reduce the sim-to-real gap and address the core deployment challenges of the real world in general-purpose robotics. The systems you help design will be exercised against real-world constraints and tested on real robotic platforms. To do this exceptionally well, we need deeper, hands-on understanding of the limitations of RL in real systems. You will look into how our model interacts with RL policies in practice and help quantify Intui’s capabilities alongside state-of-the-art RL in real-world deployments. This role is about fixing some of the largest problems within general-purpose robotics today. Our software stack is built from scratch in C/C++. We do not rely on common ML frameworks. We build what we need. The work is deep, interdisciplinary, and exploratory. You will translate theory, papers, and experimental results into robust, real-time systems that can be tested in simulation and, increasingly, on real robotic platforms through partners. What You’ll Do Explore and evaluate RL approaches in the context of robotics and embodied control of humanoid robots as well as other form factors Design and run experiments to understand the underlying model dynamics, limitations, and failure modes, especially while adapting to real-time changes Prototype and test learning-based components into low-level, real-time systems Collaborate with other research engineers to guide model development and research direction through evidence, experiments, and clear reasoning Help us understand what to test, how to test it, and why. What You Bring Strong research background, preferably a PhD, or an exceptional MSc with substantial experience in robotics and state-of-art RL / VLA models Hands-on experience applying reinforcement learning to real hardware Solid understanding of robotics fundamentals, control systems, and physical constraints Systems-level programming mindset, with proficiency in C/C++ or similar low-level languages Ability to translate papers, theory, and experimental ideas into working code and experiments that others can understand, test, and build upon Curiosity and rigor when working in poorly charted territory Bonus Signals Experience with low-level robotic control systems (e.g., PID), real-time systems, or hardware-in-the-loop setups Familiarity with sim-to-real challenges and mitigation strategies Exposure to vision-language-action models or other high-level learning systems for robotics Background in control theory or physics Who You Are Research-driven and comfortable working where answers are unclear Thoughtful, evidence-oriented, and willing to challenge assumptions, including your own Collaborative and generous with insight, not territorial about ideas Motivated by building fundamental capabilities rather than shallow demos

IntuiCell AB

This is a career-changing opportunity to work alongside world-class engineers and scientists on a mission to reimagine what machines can do. You will help us productionize cutting-edge research and integrate it with key partners. Your work will shape how intelligent machines learn, adapt, and act in the physical world. We are looking for the right person with a solid foundation, who finds learning fun and embraces deep, challenging work. Our Strategic Engagements team focuses on transforming research into products. We work in close collaboration with our partners and integrate the Intui model with their systems. This role involves tackling integration hurdles to bring our model to our partners, ensuring it supports both research and pilots effectively. As a Strategic Engagements Software Engineer, you will bridge our core AI research with client systems. You will adapt, productionize, and stabilize advanced algorithms for robust operation on diverse hardware - from embedded systems to complex platforms. This requires: Deep systems expertise to optimize high-performance native code. A hands-on approach to client deployment and resilient interface design. A focus on flexibility, creating configurable systems under strict performance constraints. What You’ll Do Translating research into a successful product hinges on several core attributes: reliability, portability, and flexibility. Additionally, success requires efficiency, developer experience, observability, and configurability. The role requires comprehensive DevOps responsibility across the entire software development lifecycle: Development: Coding, quality assurance, and testing. Infrastructure: Building CI/CD pipelines and release management. Operations: Server maintenance, system monitoring, and site reliability. What you bring Technical Stack: Strong proficiency in C++; comfortable with Python and TypeScript for integration and tooling. Systems Fluency: Expertise in Linux environments with a focus on memory management, concurrency, and performance. Engineering Mindset: You don't just write code; you design for testability and maintainability. Growth Orientation: A strong desire to adapt alongside an evolving tech stack. Bonus Signals Proficient in establishing build infrastructure. Demonstrated experience with Continuous Integration (CI). Familiarity with container technologies. Experience with Rust. Experience with CUDA. Who You Are Systems Thinker: You translate deep technical understanding into effective software solutions. Proactive Owner: You take full accountability for projects from inception to completion. Complexity Arbiter: You have a nuanced understanding of when to embrace or avoid technical complexity. Collaborative Peer: You prioritize sharing insights and ideas over territorial ownership. Builder: Your primary motivation is creating lasting, fundamental capabilities rather than superficial demos. Please note that we are strictly seeking direct individual contributors and do not work with consultants or third-party agencies.

Qlose Recruitment & Consulting AB

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.