Senior Synthetic Data Engineer - Diffusion & LoRA

NestAI; Tampere; On-site; EUR 85,000 - 110,000; Full time

Benefits offered by this job

Occupational healthcare

Epassi Flex benefit

Lunch benefit

Regular team lunches

Mac or PC

Holiday allowance

Phone benefit

Benefits expansion

Job summary

NestAI is seeking a Senior ML Engineer to join the synthetic data team within the ML Platform chapter. You will build generative pipelines and train diffusion-based models to produce realistic synthetic data for object detection in defence contexts.

You will validate results against real-world outcomes and collaborate across teams to integrate data pipelines and infrastructure. The role requires hands-on experience training generative models, working with limited data domains, and a deep

Qualifications

• Hands-on experience training generative models from scratch, not only fine-tuning.
• Experience creating synthetic data in data-scarce domains (image-based) including defense context.
• Deep familiarity with diffusion models and Python ML training frameworks, including LoRA and Diffusers.
• Ability to judge when synthetic data will impact training outcomes.
• Comfort with imperfect information in a fast-moving research area.

Responsibilities

• Build and improve generative pipelines for synthetic image/video data for object detection models.
• Train and fine-tune diffusion-based models, including LoRA.
• Combine generative data with other sources to boost realism and variation.
• Validate synthetic data against real-world outcomes to improve model training.
• Monitor new open-source models and evaluate them as they emerge.
• Collaborate with ML Platform and simulation teams on data infrastructure.

Skills

Generative modeling

Synthetic data experience

Diffusion models

LoRA

Python ML frameworks

Hugging Face Diffusers

Critical thinking

Research agility

Tools

Hugging Face Diffusers

Python

Job description

NestAI is seeking a Senior ML Engineer to join the synthetic data team within the ML Platform chapter. You will build generative pipelines and train diffusion-based models to produce realistic synthetic data for object detection in defence contexts.

You will validate results against real-world outcomes and collaborate across teams to integrate data pipelines and infrastructure. The role requires hands-on experience training generative models, working with limited data domains, and a deep