Why this grade
This listing scored 79/100, which is a B. It lost the most ground on remote clarity.
- Pay transparency 25 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 15 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Data Science Senior Full Time
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Machine Learning Engineer – RL
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $155,000–$180,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary:
We are looking for a Machine Learning Engineer - RL to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and the engineering complexity of training and evaluating policies at scale. The ideal candidate has both research depth and engineering pragmatism, with experience taking RL solutions out of the lab and into production where stability, safety, and ongoing improvement are critical.
Required Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related field; or equivalent applied experience.
- Six or more years of combined RL research and engineering experience.
- Strong proficiency in Python and modern deep learning frameworks.
- Hands-on experience with at least one major RL library or in-house RL stack.
- Solid understanding of probability, optimization, and the theoretical foundations of RL.
- Experience designing and tuning reward functions in non-trivial environments.
- Familiarity with simulation environments and large-scale experience collection.
- Experience training neural network policies on GPU clusters.
- Strong written and verbal communication skills.
- Track record of shipping or publishing impactful RL work.
Preferred Qualifications
- Experience with RLHF for large language models.
- Familiarity with multi-agent RL or hierarchical RL.
- Exposure to robotics, control systems, or autonomous driving.
- Publications in RL or related research venues.
- Open-source contributions to RL libraries or environments.
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to or contact us at (908)676-4399. Learn more about Bright Vision Technologies at .
Bright Vision Technologies is an Equal Opportunity Employer.
Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
Where this listing came from
- 01 Oct 2026 Himalayas first sighting
Seen on 1 board over 0 days.