Machine Learning Engineer - Stockholm

You know that bit where every company says they’re “changing the world”? Yeah, it can feel a little forced. But we like to think our story actually has some realness to it. Our story begins with Shadi Bitar and Ninos Malki, who came to Sweden from Syria as kids and discovered that books could be a bridge - helping them learn the language, understand the culture, and explore new worlds. A thought emerged, what if everyone could have that? And just like that, Nextory was born - your all-access pass to read, listen, and discover new perspectives without limits. And now, we're on a quest to find a Machine Learning Engineer.  Let us tell you about the role 📖 As a Machine Learning Engineer at Nextory, you'll build the systems that power how users discover, understand, and engage with books. You'll work across AI agents, search, recommendations, retrieval, and product experiences, turning advances in AI into features that users interact with every day. Some examples of what you'll be doing: * Build intelligent recommendation, search, and discovery systems that help users find their next favorite book and connect with the right content faster. * Use AI, user behavior, and content understanding to continuously improve relevance, engagement, and user experience. * Design, build, and operate scalable machine learning systems using LLMs, retrieval, recommendation, and agent technologies. * Collaborate across product and engineering teams to deliver reliable AI-powered features with measurable user impact. Your story so far 👀 We believe you're an experienced engineer who enjoys solving complex problems and turning emerging technology into products that people love using. You are comfortable moving between product thinking and technical implementation, and you thrive in environments where experimentation, ownership, and fast iteration are part of everyday work. We also believe that you have: * BSc in Computer Science or another relevant field, or equivalent work experience. * At least 3 years of experience in a similar role * Strong programming skills in Python. * Experience working with AI agents and agent-based systems. * Experience building and shipping LLM-powered features to production. The Nextory way of working 🏠 At Nextory, we believe a strong and inclusive culture is key to our success and that culture flourishes when we meet and collaborate in person as much as possible. That’s why we spend the majority of the working time at our beautiful office! We are based in Stockholm, Sweden, with offices in Paris and Bangalore. Our hybrid work policy includes four days in the office and Wednesdays as a work-from-home day. Your next story starts here 💫 We look forward to your application 💫. Applications are reviewed continuously, but please note that due to summer vacations, our response times may be a little longer than usual. If you have any questions about the role, please contact erika.thorslund@nextory.com. Please note that we do not offer relocation and that a six-month probationary period applies.

Modulai works with fish, trains, clothes, money, pets, office spaces, sound sensors and much more. If there is data, we do ML (Machine Learning) on it. Our team consists of devoted ML engineers with strong track records from some of Sweden’s most successful startups. We work on project basis and take end-to-end responsibility. We love ML and we think that the best way for us to expand our knowledge is to be exposed to a diversified set of challenging and fun projects. MACHINE LEARNING ENGINEER As a member of the ML-team you will be working with a broad range of problems with one common denominator – ML will be the key ingredient. The projects could be external as well as internal – and in all cases – delivery is central. You will have to analyze the problem at hand, come up with a solution strategy and execute on it. This typically entails gaining an in-depth understanding of the challenge, understanding the available data and then re-formulating it as a ML problem. It requires openness, creativity and an eagerness to learn new methodology and exploring new terrains. We frequently attack these problems as a team, meaning that you will have to be able to clearly explain your reasoning and code in order to engage the rest of us. Our Stack Python / R – standard open-source libraries Scikit-learn and various specialized Python and R ML libraries Large Language Model (LLM) frameworks such as LangChain/LlamaIndex, LangGraph, CrewAI Cloud platforms such as AWS, GCP, and Azure CI/CD: DVC, Github Actions, Sagemaker/VertexAI/AzureML, Relational database management systems MLOps and LLMOps tools for model deployment and monitoring. Software engineering best practices, including testing, version control (Git), and containerization (Docker, Kubernetes) Orchestration: Airflow, AWS Step functions, etc Engineering/LLM/deployment: Kubernetes, docker, terraform Responsibilities Analyzing and planning problems, solutions, and delivery with stakeholder managment, and communication with client Preprocessing, feature engineering, and dataset creation ML and LLM model development, fine-tuning, and evaluation Validation of results and model interpretability Building and optimizing data pipelines and ML/LLM infrastructure Developing APIs and integrating ML models into production systems Ensuring scalability, monitoring, and performance optimization of deployed models Background & Skills MSc or Ph.D. in a quantitative field Excellent understanding of a broad set of ML and deep learning algorithms, including LLMs Strong software development skills in Python and experience with software engineering best practices Experience deploying ML and LLM models into production environments A passion for lean, clean, and maintainable code The desire to grow and to share insights with others Helpful Knowledge Deep learning frameworks and transformer-based architectures LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) Data pipelining and ML/LLM infrastructure best practices DevOps experience, CI/CD, Kubernetes, and serverless architectures Experience with vector databases e.g (Pinecode, redis, and ElasticSearch) for LLM applications About Team Modulai At Modulai we focus 100% on solving problems with machine learning (ML). We work in teams on a project basis. We work for clients, as part of the core team in startups where we have long-time engagement as well for large enterprises transforming ways of working. Learning and teamwork are central to how we work. Everyone in the team is or will soon be a full-stack ML engineer capable of scoping and developing end-to-end ML solutions. You should be able to do end-to-end machine learning products by yourself but actually, never do it because we always work in teams. If there is data, we will do ML on it! Apply here: https://modulai.teamtailor.com/