Bright Vision Technologies

Bright Vision Technologies

Reinforcement Learning Engineer

Clarksburg, Maryland · Senior · Full-time

H1B sponsorship availableDetected 124 days ago
PythonAlgorithmsMachine LearningDeep LearningLLMsRoboticsControlsResearchCommunication

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odds of building a lasting career here

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Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

13 transfer filings in the last year, covering 13 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • 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.

Responsibilities

  • Develop, calibrate, and maintain simulation environments suitable for large-scale agent training.
  • Implement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL methods.
  • Build scalable training infrastructure for distributed RL, including efficient experience collection and replay systems.
  • Optimize training stability and sample efficiency through algorithmic and engineering improvements.
  • Design rigorous evaluation protocols, including out-of-distribution and adversarial test cases.
  • Implement safety mechanisms such as constraint enforcement, conservative policies, and human-in-the-loop oversight.
  • Collaborate with applied scientists and product teams to identify high-value RL use cases.
  • Monitor deployed policies and models in production for drift, regression, and unintended behaviors, building the alerting and dashboards that surface issues before they meaningfully affect users.
  • Document methodology, design decisions, and operational characteristics for internal stakeholders.
  • We will support H1B transfers for qualified candidates.

Requirements

  • Six or more years of combined RL research and engineering experience.
  • Hands-on experience with at least one major RL library or in-house RL stack.
  • 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.
  • Track record of shipping or publishing impactful RL work.

Nice to have

  • 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.

Skills

  • This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
  • Reinforcement Learning Engineer
  • Salary Range:
  • 100k$/Annum-150k$/Annum
  • 100% Remote (Continental United States)
  • In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
  • Sponsorship:
  • No new H1B sponsorship available.
  • H1B transfers welcomed for qualified candidates.
  • Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
  • Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap

Compensation

  • Competitive base salary commensurate with experience, plus benefits.

Benefits

  • Design and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments.
  • Apply offline RL and imitation learning techniques where exploration is costly or unsafe.
  • Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
  • This role is part of Bright Vision Technologies' in-house Statement of Work (SOW) engagement.
  • The client, end customer, and employer for this position is Bright Vision Technologies - there is no third-party client, vendor, or implementation partner involved.
  • Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
  • We are looking for a Reinforcement Learning Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient.
  • Learn more about Bright Vision Technologies at www.bvteck.com.
  • We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
  • Bright Vision Technologies is an
  • Equal Opportunity Employer, including Disability/Veterans.

Company info

  • As we continue to grow, we're looking for a skilled Reinforcement Learning Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.
  • We are an equal opportunity employer and place a high value on diversity and inclusion at our company.

Equal opportunity

  • equal opportunity employer and place a high value on diversity and inclusion at our company.
  • Equal Employment Opportunity (EEO) Statement

Visa & Work Authorization

  • No new H1B sponsorship available.
  • H1B transfers welcomed for qualified candidates.
  • Employment Terms & Visa Policy
  • No new H1B sponsorship is available for this role.
  • However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply.
  • We will support H1B transfers for qualified candidates.
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This listing is sourced directly from Bright Vision Technologies's careers page and normalized into a canonical job model.