AI Engineer, RL Environments — Scale Sandboxed Training (Equity)

Hashlist; Helsinki; On-site; EUR 80,000 - 120,000; Full time

Benefits offered by this job

Competitive compensation

Meaningful equity

Central office in Helsinki

Work with model providers

Job summary

Hashlist expands its AI research team in Helsinki to develop domain-specific RL environments for constrained embedded programming and enterprise workflows. You will build and automate platforms for RL environments and simulate worlds to reveal model weaknesses.

You will translate training objectives into concrete data and evaluation specs, construct the reward layer, and run large-scale sandbox rollouts while collaborating with OEMs and AI Labs on fine-tuning challenges.

Qualifications

• Production ML depth with Python and PyTorch for RL training.
• End-to-end RL environment built and model trained.
• Experience with containerization tools like Docker and scaling systems.
• Strong communication and motivation.

Responsibilities

• Build and automate our platform for creating RL environments.
• Construct simulated worlds and expose model failure modes.
• Turn AI objectives into concrete data and evaluation specs.
• Build the reward layer and mitigation for reward hacking.
• Run rollouts at scale with hundreds of sandboxed attempts.
• Fine-tune open-source models and export datasets.
• Communicate with OEMs and AI Labs on research questions.

Skills

Python

PyTorch

Reinforcement learning

TRL

OpenRLHF

LoRA fine-tuning

vLLM

SGLang

PPO

Docker

Tools

Docker

Job description

Hashlist expands its AI research team in Helsinki to develop domain-specific RL environments for constrained embedded programming and enterprise workflows. You will build and automate platforms for RL environments and simulate worlds to reveal model weaknesses.

You will translate training objectives into concrete data and evaluation specs, construct the reward layer, and run large-scale sandbox rollouts while collaborating with OEMs and AI Labs on fine-tuning challenges.