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Vice President Deep Reinforcement Learning Jobs (NOW HIRING)

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving ... This engineer will leverage their deep expertise in RL to solve critical locomotion and ...

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How much do vice president deep reinforcement learning jobs pay per year?

As of Jul 12, 2026, the average yearly pay for vice president deep reinforcement learning in the United States is $157,532.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $190,000.00 per year, depending on experience, location, and employer.
What cities are hiring for Vice President Deep Reinforcement Learning jobs? Cities with the most Vice President Deep Reinforcement Learning job openings:
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What states have the most Vice President Deep Reinforcement Learning jobs? States with the most job openings for Vice President Deep Reinforcement Learning jobs include:

Senior Machine Learning Engineer - Deep & Reinforcement Learning

Kanak Elite Services Inc

Houston, TX • On-site

$99K - $137K/yr

Contractor

Re-posted 26 days ago


Job description

Hello There,

My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of Senior Machine Learning Engineer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com .

Job Description

Position           : Senior Machine Learning Engineer – Deep & Reinforcement Learning

Location          : Houston, TX Onsite

Duration         : Long term contract

Required skills:
- Degree in STEM field, Ph.D preferred.
- Master in Deep Learning, Reinforcement Learning, and multimodal large language model.
- Strong Pytorch or TensorFlow programming
- Machine Learning and Statistical Modelling - Mastery
- Exploratory Analysis
- Core Programming Skills & Languages
- AI Engineering Essentials
- DevOps and Agile
- Cloud deployment frameworks, infrastructure, and tooling