ML Research Engineer
Aliant is looking for an experienced ML Research Engineer for an exciting consulting assignment.
You will join a senior R&D team working on advanced challenges in Machine Learning, Generative AI and Speech AI, helping transform research into scalable production systems.
This is an excellent opportunity for someone who enjoys solving complex technical problems, experimenting with modern AI technologies and taking ownership from idea to implementation.
About the assignment
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 engineers and researchers on technical decisions, research initiatives and product development.
We are looking for someone who has:
Strong Python programming skills.
Solid software engineering fundamentals.
Hands-on experience with Machine Learning and modern Generative AI/LLMs.
The ability to drive technical challenges from concept to implementation.
Strong communication and collaboration skills.
Experience using modern AI tools to accelerate software development.
Meritorious experience
Experience in one or more of the following areas is highly valued:
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 optimization.
Speech recognition (ASR), Text-to-Speech or other Audio AI technologies.
Research experience, scientific publications or significant open-source contributions.
As a person, you are curious, pragmatic and collaborative. You enjoy exploring new technologies, challenging assumptions and continuously improving both your own work and the technology around you.
Assignment information
Start: ASAP (after the summer)
Location: Helsingborg – Hybrid - 2 days onsite per week
Workload: Full-time