Researcher, Post Training

Lovable; Stockholms kommun; On-site; SEK 600,000 - 800,000; Full time

Job summary

Lovable is a fast-growing AI company based in Stockholm, seeking an experienced engineer to lead the post-training pipeline for large language models. You will own the lifecycle from data curation to deployment, ensuring that promising research translates to user-facing improvements quickly.

The ideal candidate has strong production coding skills, experience with ML frameworks, and a track record in model evaluation and optimization. Join us to redefine software creation!

Qualifications

• Experience running post-training jobs on large language models.
• Ability to write reliable production code.
• Fluent in a major ML framework.
• Understanding of techniques in preference optimization and alignment.

Responsibilities

• Own the full lifecycle of the post-training pipeline.
• Apply reinforcement learning and supervised tuning methods.
• Develop deployment systems for training jobs.
• Investigate and resolve failures end-to-end.

Skills

Post-training on large language models

Production code writing

Fluency in ML frameworks (PyTorch, JAX)

Understanding of preference optimization

Contributed to evaluation systems

Trace model quality regressions

Shipping products quickly

Job description

TL;DR: Lovable lets over 2 million people build software using plain language, and the models behind it need to be exceptional. We're hiring an engineer who has gotten their hands dirty with post-training at scale and wants to do it again for one of the fastest-growing AI products in the world.

You’ll own our full post-training pipeline: translating the latest research into production training recipes, adapting them for code generation and agent workloads, and putting improved models in front of users fast. The goal is to get promising research into production within days or weeks, not months. This isn't an academic research position - you'll spend as much time in production infrastructure as in training configs, and your success is measured by what ships.

Why Lovable?

Lovable lets anyone and everyone build software with any language. From solopreneurs to Fortune 100 teams, millions of people use Lovable to transform raw ideas into real products - fast. We are at the forefront of a foundational shift in software creation, which means you have an unprecedented opportunity to change the way the digital world works. Over 2 million people in 200+ countries already use Lovable to launch businesses, automate work, and bring their ideas to life. And we’re just getting started.

We’re a small, talent-dense team building a generation-defining company from Stockholm. We value extreme ownership, high velocity, and low-ego collaboration. We seek out people who care deeply, ship fast, and are eager to make a dent in the world.

What we’re looking for

• You've personally run post-training jobs on large language models - RFT/RLVR, preference optimization, or similar. Not just called APIs or written prompts, but actually trained and iterated on models
• You can write solid production code. The systems you build need to run reliably, not just produce interesting research artifacts
• You're fluent in at least one major ML framework (PyTorch, JAX) and comfortable working with distributed training setups and GPU clusters
• You understand the math behind preference optimization, reward modeling, and alignment techniques - and can reason about when each approach fits
• You've built or significantly contributed to evaluation systems that capture real-world quality, not just benchmark scores
• You can trace a model quality regression from user-facing symptoms back through serving, inference, and training - and you enjoy doing it
• You want to ship. Research taste matters, but at Lovable the question is always "how fast can we get this to users?"

Preferred

• You've worked on code generation or agentic use cases specifically
• You've put post-trained models into the hands of real users and seen how they hold up at scale
• You've owned the full loop: curating data, running training, evaluating results, deploying, and monitoring in production
• You have a habit of reading a paper on Monday and having a prototype running by Friday
• You've experimented with speculative decoding or similar techniques to improve model efficiency
• You have strong views on evaluation methodology and have built evals that actually predict user satisfaction
• You've published or contributed meaningfully to the open-source ML ecosystem

What you’ll do

Own the full lifecycle of Lovable's post-training pipeline - from data curation and training runs through evaluation and deployment

Apply and adapt reinforcement learning, preference optimization, and supervised fine-tuning methods to make our models better at generating code, reasoning about user intent, and acting as reliable agents

Build the evaluation and experimentation infrastructure that tells us whether a model change actually helps users - covering helpfulness, safety, latency, and reliability

Develop and operate the production systems that run training jobs at scale, including GPU orchestration and data pipelines

Work across team boundaries with our agent, product, and infrastructure engineers to turn model gains into product improvements users can feel

Investigate and resolve failures end-to-end - whether the root cause is in a training recipe, a data issue, or a serving regression

Read papers, run experiments, and move fast: the goal is to get promising research into production within days or weeks, not months

About your application

Please submit your application in English. It’s our company language, so you’ll be speaking lots of it if you join.

We treat all candidates equally - if you’re interested, please apply through our careers portal.

Ready to join us?

Help us unlock human creativity and build the future of software creation.