Senior Machine Learning Engineer
Hybrus ABSammanfattning
We are seeking a Senior ML Engineer for a long-term assignment in Stockholm, focusing on optimizing the training and deployment of machine learning models, particularly for mobile devices. The role involves collaboration with various teams to establish best practices and explore innovative solutions like federated learning. This position is primarily onsite with potential hybrid options, and the contract duration is between 6 months to 1 year.Jobbet i korthet
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visstid
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heltid
Ansök senast: 2026-07-29
Publicerad: 2026-06-29
Beskrivning
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.
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.
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Senior Machine Learning Engineer
OM FÖRETAGET
Hybrus AB
