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Hire Mid-Level Reinforcement Learning Engineers

Browse 94 vetted Mid-Level Reinforcement Learning engineers available for remote hire. Every profile is manually reviewed — only real production experience gets listed.

94 Mid-Level Reinforcement Learning profiles
Manually reviewed
Remote worldwide

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Jahir

Jahir

Mid-Level
India — Kolkata (UTC+5.5) Full-time, Part-time
AI & Machine Learning Engineers NLP & Prompt Engineering
Raza

Raza

Mid-Level
Pakistan — Karachi (UTC+5) Active 18 hours ago Full-time, Part-time
AI Product & Strategy Automation & AI Workflows
Oluwajuwon

Oluwajuwon

Mid-Level
Nigeria — Lagos (UTC+1) Full-time, Freelance
AI & Machine Learning Engineers data science & analytics
Tejaswi

Tejaswi

Mid-Level
India — Kolkata (UTC+5.5) Full Time
AI & Machine Learning Engineers
Tanmay

Tanmay

Mid-Level
India — Kolkata (UTC+5.5) Freelance, Part-time
AI Business, Marketing & Strategy Automation & AI Workflows
Shuntoria

Shuntoria

Mid-Level
United States — Chicago (UTC-5) Full-time, Part-time
AI & Machine Learning Engineers NLP & Prompt Engineering
Zia

Zia

Mid-Level
Pakistan — Karachi (UTC+5) Contract, Full-time
AI & Machine Learning Engineers data science & analytics
Leloko

Leloko

Mid-Level
South Africa — Johannesburg (UTC+2) Full-time, Contract
AI & Machine Learning Engineers AI Implementation & Consulting
Carlos M.

Carlos M.

Mid-Level
United States — New York (UTC-4) Contract, Contract-to-hire
NLP & Prompt Engineering Automation & AI Workflows
Manan

Manan

Mid-Level
India — Kolkata (UTC+5.5) Contract, Full-time
AI & Machine Learning Engineers data science & analytics

About this role

What makes a Mid-Level Reinforcement Learning engineer?

Reinforcement learning engineers work on one of the most technically challenging areas of AI — training agents to make optimal decisions through experience. Applications include robotics, game AI, recommendation systems, trading, and RLHF for LLM alignment.

Frequently asked questions

What makes a Mid-Level Reinforcement Learning engineer the right hire?

Mid-level Reinforcement Learning engineers work independently on most tasks, contribute to architecture discussions, and require less hand-holding than juniors. They offer a strong balance of productivity and cost for companies that need reliable execution without the premium of a senior hire.