Magnet Forensics is a global leader in the development of digital investigative software that acquires, analyzes, and shares evidence from computers, smartphones, tablets, and IoT-related devices. We are continually innovating so our customers can deploy advanced and effective tools to protect their companies, communities, and countries. Serving thousands of customers globally, our solutions are playing a crucial role in modernizing digital investigations, helping investigators fight crime, protect assets, and guard national security. With employees based around the world, Magnet Forensics has been expanding our global presence. As a part of Magnet Forensics, you can expect to make a difference in the world, no matter what role you play. You’ll be supported through learning and development, not to mention an incredible team with unbelievable talent and integrity. If you think you would be the right person to join our team working towards this goal, we would love to hear from you!
Your RoleWe are looking for a Senior Machine Learning Engineer to join our AI Research team, designing, experimenting with, and optimizing cutting-edge ML models that power our digital forensics capabilities. You will lead the development of new models, training techniques, and evaluation methods that surface critical leads and insights for investigators, helping them solve cases faster and with greater confidence. As part of the Research team, you’ll work closely with Product, UX, and our Brain team to ensure our models push the boundaries of what’s possible, while remaining practical for real-world use. You’ll own complex ML projects end-to-end, including ideation and experimentation, to evaluation and handoff for integration, working with our team to advance the state-of-the-art in digital forensics.
What You Will Accomplish:
- Design, implement, and evaluate state-of-the-art machine learning models. Lead experiments, define metrics, and iterate to improve performance, efficiency, and reliability;
- Collect, build, and work with complex, real-world datasets, developing preprocessing, augmentation, and feature engineering techniques that enhance model training and fairness;
- Collaborate cross-functionally with our Brain team to ensure models are production-ready, scalable, and meet real user needs.
- Stay at the forefront of ML research, assessing new techniques, frameworks, and trends, and translating them into practical innovations for our products;
- Mentor other engineers on ML best practices, experimental design, and technical decision-making;
- Contribute to building reusable research infrastructure and tooling that accelerates experimentation and improves reproducibility;
- Ensure ethical and responsible AI practices are integrated into model design, training, and evaluation.
Why You’ll Love This Role:
- In your first 90 days, you’ll get hands-on with our Research team, experimenting with real-world datasets and evaluation pipelines to improve the accuracy, efficiency, or robustness of our models. You’ll collaborate closely with Product, UX, and Brain to ensure your work addresses investigator needs and is ready for integration into production systems. By the end of your first three months, you’ll have taken ownership of a key research initiative, delivering results that directly advance our AI capabilities and lay the groundwork for future innovations.
What We Are Looking For:
- We’re looking for someone who checks off most, but not all, of the boxes listed in “skills and experiences”. It’s more important to us to find candidates who can display indicators of success through skills they have developed and experiences they have been a part of, than to find folks who have ‘been there, done that”. We want to be part of your development journey, and we’ll learn as much from you as you learn from us.
Required Skills:
- 5+ years of professional experience in machine learning or applied AI, with a track record of delivering models into production or production-ready pipelines;
- Strong Python programming skills, with experience in building maintainable, scalable ML codebases;
- Experience designing and running experiments, selecting appropriate evaluation metrics, and interpreting results to guide iteration;
- Hands-on experience with deep learning frameworks (eg, PyTorch, TensorFlow) and deployment frameworks (eg, Triton, TorchServer);
- Experience working with large, complex, and/or unstructured datasets;
- Understanding of the trade-offs between model complexity, accuracy, training cost, and inference speed;
- Ability to work cross-functionally with engineers, researchers, product managers, and designers;
- Strong communication skills for both technical and non-technical audiences;
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience in applied ML research and engineering.
Nice to Have:
- Experience with self-supervised, multimodal, or retrieval-augmented learning approaches;
- Background in NLP, computer vision, or other relevant ML domains;
- Familiarity with MLOps tooling (eg, experiment tracking, model versioning, CI/CD for ML);
- Experience mentoring engineers or leading ML research initiatives;
- Contributions to open-source ML projects or publications in peer-reviewed venues;
- Experience working with cloud providers like AWS or Azure is an asset.
The Most Important Thing:
- We’re looking for candidates that can provide examples of how they have demonstrated Magnet CODE in their previous experiences:
- CARE – We care about each other and our mission to make a difference in the world.
- OWN – We are accountable for our results – while never forgetting to act with integrity, empathy, and respect.
- DEDICATE – We put our heart and soul into meeting the needs of our customers and helping them serve the people they protect.
- EVOLVE – We are constantly innovating and exploring new ways to work together to make an impact with our work.
Compensation & Benefits
- The Compensation Range is for the primary location for which the job is posted. Please note that the actual compensation may vary depending on location and job-related factors such as qualifications, experience, knowledge and skills. If you are applying for this role outside of the primary location and you are selected for an interview, the Talent Acquisition Partner can share more information with you. If the compensation structure for the role includes an incentive component (ie. most Sales roles) the range below represents total target compensation (TTC) (base salary + variable)
Compensation Range:
- MIN: 623,000 - MID: 890,000 - MAX: 1,068,000 SEK
Magnet is proud to offer benefits such as:
- Generous time off policies
- Competitive compensation
- Volunteer opportunities
- Reward and recognition programs
- Employee committees & resource groups
- Healthcare and retirement benefits
All offers of employment at Magnet are contingent upon satisfactory completion of a background check. All background checks will be conducted in accordance with all applicable laws. Magnet will consider each position’s job duties, among other factors, in determining what constitutes satisfactory completion of the background check. Refusal to consent to a background check may be grounds for revoking an offer of employment.
US Applicants: Magnet Forensics participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
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