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Overview
Principle AI Researcher/Engineer - (LLM reinforcement learning) in Helsinki, Finland - AMD - Remote - Finland
Researcher
Salary Context: Researcher
Market Average: Researcher
€7,234 - €23,873
Market Average: this role level Level
€7,234 - €8,319
Estimated Offer
€7,234 - €8,319
€7,234€23,873
per month
Location
Remote - Finland
Remoteness
Remote
Estimated Expiry
February 10, 2026
Posted: January 6, 2026
Role Level
Mid-Level
Management Tier
No People Management
Job Type
Full-time
Job Description
Join AMD's Silo AI team to work on open source post-training models, focusing on multilingual and low-resource performance, using reinforcement learning and reward modeling.
Company Information
Technology
Data shown is based on historical job postings from our database.
Job Details
Requirements
- Experience with post-training environments
- Knowledge of reward modeling and RL at scale
- Research or engineering contributions
- Statistics, optimization, error analysis
Responsibilities
- Design and tune post-training methods
- Develop synthetic-data pipelines
- Collaborate on open source projects
- Improve post-training performance
Field:
Technology
Education Level
Masters
No items to show.
6 days ago
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Overview
Principle AI Researcher/Engineer - (LLM reinforcement learning) in Helsinki, Finland - AMD - Remote - Finland
Researcher
Salary Context: Researcher
Market Average: Researcher
€7,234 - €23,873
Market Average: this role level Level
€7,234 - €8,319
Estimated Offer
€7,234 - €8,319
€7,234€23,873
per month
Location
Remote - Finland
Remoteness
Remote
Estimated Expiry
February 10, 2026
Role Level
Mid-Level
Management Tier
No People Management
Job Type
Full-time
Posted: January 6, 2026
Job Description
Join AMD's Silo AI team to work on open source post-training models, focusing on multilingual and low-resource performance, using reinforcement learning and reward modeling.
Company Information
AMD
Technology
Data shown is based on historical job postings from our database.
Job Details
Requirements
- Experience with post-training environments
- Knowledge of reward modeling and RL at scale
- Research or engineering contributions
- Statistics, optimization, error analysis
Responsibilities
- Design and tune post-training methods
- Develop synthetic-data pipelines
- Collaborate on open source projects
- Improve post-training performance
Field:
Technology
Education Level
Masters
No items to show.
6 days ago