{"id":3019902,"url":"https://alion.io/job/bright-vision-technologies-ai-learning-systems-engineer-bright-vision-technologies-7","title":"AI Learning Systems Engineer - Bright Vision Technologies","company":{"id":452187,"name":"Bright Vision Technologies","domain":"brightvisiontechnologies.com","url":"https://alion.io/company/bright-vision-technologies-2","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":100000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"DPO","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Imitation Learning","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reward Modeling","optional":false},{"name":"RLHF","optional":false},{"name":"AI Agents","optional":true}],"status":"live","first_seen_at":"2026-10-21T17:33:37Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-21T22:41:33Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"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.\nAs 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.\nThis is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.\nJob Title: AI Learning Systems Engineer\n Location: 100% Remote (Continental United States)Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)\nExperience: 6+ years\nSalary: $100K- $150K\nEmployment Terms & Visa Policy\nThis is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.\nThis 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.\nWe do not engage in C2C, 1099, or third-party arrangements for this role.\nCandidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.\nNo new H1B sponsorship is available for this role.\nHowever, 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.\nFor every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.\nJob Summary\nWe 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.\nKey Responsibilities\nDesign and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments.\nDevelop, calibrate, and maintain simulation environments suitable for large-scale agent training.\nImplement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL methods.\nEngineer reward functions and shaping strategies that align agent behavior with desired outcomes and safety constraints.\nApply offline RL and imitation learning techniques where exploration is costly or unsafe.\nUse RLHF, DPO, and related techniques for fine-tuning large language models when relevant.\nBuild scalable training infrastructure for distributed RL, including efficient experience collection and replay systems.\nOptimize training stability and sample efficiency through algorithmic and engineering improvements.\nDesign rigorous evaluation protocols, including out-of-distribution and adversarial test cases.\nImplement safety mechanisms such as constraint enforcement, conservative policies, and human-in-the-loop oversight.\nCollaborate with applied scientists and product teams to identify high-value RL use cases.\nMonitor 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.\nDocument methodology, design decisions, and operational characteristics for internal stakeholders.\nStay current with RL research and translate promising techniques into production-ready solutions.\nRequired Qualifications\nMaster’s or PhD in Computer Science, Machine Learning, or a related field; or equivalent applied experience.\nSix or more years of combined RL research and engineering experience.\nStrong proficiency in Python and modern deep learning frameworks.\nHands-on experience with at least one major RL library or in-house RL stack.\nSolid understanding of probability, optimization, and the theoretical foundations of RL.\nExperience designing and tuning reward functions in non-trivial environments.\nFamiliarity with simulation environments and large-scale experience collection.\nExperience training neural network policies on GPU clusters.\nStrong written and verbal communication skills.\nTrack record of shipping or publishing impactful RL work.\nPreferred QualificationsExperience with RLHF for large language models.\nFamiliarity with multi-agent RL or hierarchical RL.\nExposure to robotics, control systems, or autonomous driving.\nPublications in RL or related research venues.\nOpen-source contributions to RL libraries or environments.\n How to ApplyWould you like to know more about this opportunity?\nFor immediate consideration, please send your resume to  or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com.\nWe 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.\nWe 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.\nBright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.\nPosition offered by “No Fee Agency.”\nEqual Employment Opportunity (EEO) Statement\nBright 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.\nBV Teck expressly prohibits any form of workplace harassment or discrimination. 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