AI Learning Systems Engineer

Bright Vision Technologies; Highlands Ranch (CO); Remoto; USD 100.000 - 150.000; Tempo pieno

Descrizione del lavoro

Bright Vision Technologies is seeking an AI Learning Systems Engineer to design, train, and deploy RL-based systems for high-impact decision tasks. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and production-grade engineering to ensure stability and safety.

You will work with applied scientists and product teams to identify valuable RL use cases, build scalable training infrastructure, and monitor deployed policies

Competenze

• Master’s or PhD in CS/ML or equivalent practical experience.
• 6+ years of RL research and engineering experience.
• Strong Python and modern deep learning frameworks.
• Experience with at least one major RL library or in-house RL stack.
• Experience training neural policies on GPU clusters.
• Excellent written and verbal communication; track record of RL work.

Mansioni

• Design and implement RL solutions for sequential decision-making problems.
• Develop and maintain simulation environments for large-scale training.
• Evaluate RL algorithms including policy gradient, actor-critic, off-policy, and offline RL.
• Engineer reward functions and shaping strategies aligned with safety goals.
• Apply offline RL and imitation learning where exploration is costly.
• Use RLHF, DPO for fine-tuning LLMs when relevant.
• Build scalable training infrastructure for distributed RL.
• Optimize training stability and sample efficiency.
• Design rigorous evaluation protocols (OOD/adversarial tests).
• Implement safety mechanisms and human-in-the-loop oversight.
• Collaborate with applied scientists and product teams on high-value use cases.
• Monitor deployed policies for drift; build dashboards and alerts.
• Document methodology and operational characteristics for stakeholders.
• Stay current with RL research and production-ready techniques.

Conoscenze

Python

Deep learning

Reinforcement Learning

Communication

GPU usage

Probability & optimization

Formazione

MS/PhD in CS/ML

Strumenti

RL library

In-house RL stack

Simulation environments

Descrizione del lavoro

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.

As we continue to grow, we’re looking for a skilled AI Learning Systems Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.

This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: AI Learning Systems Engineer

Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Experience: 6+ years
Salary: $100K- $150K

Employment Terms & Visa Policy

This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
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.
We do not engage in C2C, 1099, or third-party arrangements for this role.
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.
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.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands‑on experience.

Job Summary

We are looking for an AI Learning Systems Engineer 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.

Key Responsibilities

• Design and implement reinforcement learning solutions for sequential decision‑making problems in real and simulated environments.
• 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.
• Engineer reward functions and shaping strategies that align agent behavior with desired outcomes and safety constraints.
• Apply offline RL and imitation learning techniques where exploration is costly or unsafe.
• Use RLHF, DPO, and related techniques for fine‑tuning large language models when relevant.
• 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.
• Stay current with RL research and translate promising techniques into production‑ready solutions.

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.

We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. 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.

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.