• Develop scalable Python services and production-grade APIs • Design, implement, and improve AI features using LLMs and modern ML techniques • Build specialized edge models • Create unique labeling strategies and coach labeling of data to support model building. • Take AI systems from concept and prototype to reliable, observable, production deployments • Collaborate closely with product, founders, and stakeholders to shape product direction • Continuously improve system architecture, data pipelines, and ML/AI infrastructure

• Build LLM-based applications. • Develop conversational systems and semantic search and integrate them into the domain-specific applications of the industry solution. • Set up and maintain RAG (Retrieval-Augmented Generation) systems. • Including knowledge-base management: indexing, updates, and clean, source-separated storage of structured and unstructured content. • Operation and monitoring. • MLOps in production: observability, structured logging, and error analysis. • Ensure systems run reliably in production, not just that they worked once. • Deploy agents into production. • From development through integration and connection to portal systems to stable delivery. • Improve solutions based on data. • Use monitoring data, tests, and user feedback to iteratively improve solutions. • Experiment with new approaches. • Identify new AI use cases, prototype them, and build data pipelines from preprocessing and model development to production.

Role Description 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. 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. 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 [email protected] or contact us at (908) 676-4399. Learn more about Bright Vision Technologies at www.bvteck.com . 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.

Role Description The Senior Presentation Associate position is responsible for providing presentation services for our clients. - Utilize appropriate logs and/or tracking software for all presentation work. - Thoroughly assess job request and ensure appropriate completion of job tasks throughout task lifecycle. - Perform work in presentation design, including, but not limited to: - Creating pitch books and materials. - Creating, editing, and error correcting multiple document types to support the client’s brand. - Intake and workflow coordination functions, as needed. - Exercise independent judgment & use established procedures, standards, and formats to edit, proof, create, or otherwise complete presentation requests to client satisfaction. - Demonstrate proficiency in using equipment/technology/software and hardware necessary to perform job functions. - Communicate with team members, lead, supervisor, or client on job or deadline concerns. - Meet contracted deadlines for service delivery to our clients. - Troubleshoot basic software or hardware problems. - Help to foster a proactive environment of continuous service enhancement and relationship building with the client. - Perform Quality Assurance on own work and/or work of others, as requested. - Adhere to Williams Lea Tag policies, in addition to client policies. - Use equipment and supplies in a cost-efficient manner. Qualifications - High school diploma or equivalent. - 3+ years’ presentation experience preferably in a legal, banking, or large corporate environment. - Advanced skill in the use of MS Office software (Excel, PowerPoint, Visio as examples); strong keyboarding and typing skills. - Adept with other software programs for editing and/or creating documents; specifically, Adobe PDF & Creative Suite (Illustrator, Photoshop as examples). - Strong attention to detail; able to work on multiple projects simultaneously. - Able to apply intermediate to advanced requisite knowledge of appropriate grammar, spelling, composition to work requests. - Must have good organizational skills. - Must be able to meet deadlines and complete all projects in a timely manner. - Ability to handle sensitive and/or confidential documents and information. - Able to exercise good judgment to make decisions that conform to business needs and policy. - Able to troubleshoot more complex or advanced tasks, equipment, or software concerns on own; understands when to escalate a problem to a supervisory level. - Ability to maintain professional composure when working with immediate deadlines. - Ability to work both independently and collaboratively as part of a team. - Ability to work in a fast-paced environment. - Ability to communicate professionally both verbally and in writing. - Must be self-motivated with a positive attitude. - Proven customer service skills are required in order to create, maintain, and enhance customer relationships. Requirements - Position operates at sites with maximum of 24/7 operations. Individual shift requirements will vary by site. - Ability to work overtime as needed. - Work is performed in a professional work environment. - Professional/business casual attire required. - Hazards include working with office machines (computers, peripherals, copiers, faxes, scanners, bindery equipment, paper cutters, paper, toner) and cleaning supplies. - Must be able to work sitting down most of the time. Benefits - Medical, dental, and vision coverage. - Paid time off. - Disability insurance. - 401(k) with company match. - Life insurance and other voluntary supplemental insurance coverages. - Parental leave. - Adoption assistance. - Tuition assistance. - Employer/partner discounts.