Role Description We are seeking an AI Innovation Engineer to bridge cutting-edge applied research and production engineering, designing and shipping advanced machine learning systems that solve high-impact business problems. The role blends scientific rigor with practical software engineering, requiring deep understanding of modern ML and deep learning techniques alongside the ability to build robust, scalable, and well-instrumented production pipelines. The ideal candidate stays current with the rapidly evolving AI research landscape, can critically evaluate new techniques for real-world applicability, and is comfortable operating across the full lifecycle from problem framing and experimentation to deployment and continuous improvement. Key Responsibilities - Design, prototype, and evaluate applied AI solutions across natural language, vision, recommendation, and structured data domains. - Translate ambiguous business problems into well-scoped ML formulations with clear success metrics and evaluation strategies. - Stay current with the latest research in deep learning, large language models, and adjacent areas, and assess applicability to internal use cases. - Implement rigorous experimentation workflows including baselines, ablations, and statistically sound evaluation methodology. - Build production-quality training and inference pipelines using modern ML frameworks and orchestration tools. - Collaborate with ML platform engineers to ensure efficient use of compute, storage, and accelerator resources. - Optimize models for accuracy, latency, throughput, and cost based on production requirements. - Develop tooling for dataset construction, labeling, validation, and ongoing monitoring of data quality. - Partner with product, design, and domain experts to ensure model behavior aligns with user needs and policy requirements. - Implement safety, fairness, and reliability evaluations and incorporate findings into model selection decisions. - Document research findings, design decisions, and operational characteristics clearly for both technical and non-technical audiences. - Mentor engineers on applied ML methodology, evaluation rigor, and responsible deployment. - Contribute to internal knowledge sharing, reading groups, and prototype-to-production playbooks. - Influence the broader AI roadmap based on research insight, capability gaps, and emerging opportunities. Qualifications - Master’s or PhD in Computer Science, Machine Learning, Statistics, or a closely related field; or equivalent applied experience. - Six or more years of combined research and applied ML engineering experience. - Strong proficiency in Python and modern ML frameworks such as PyTorch or JAX. - Hands-on experience training, fine-tuning, and evaluating deep learning models at non-trivial scale. - Solid grounding in mathematics, statistics, and the theoretical foundations of modern ML. - Experience taking ML models from research prototype to production with appropriate observability and safeguards. - Familiarity with distributed training, mixed-precision training, and accelerator hardware. - Strong written and verbal communication skills, including ability to explain complex methods clearly. - Demonstrated ability to read, evaluate, and adapt techniques from current research literature. - Track record of shipping impactful applied AI projects. Preferred Qualifications - Published research at top-tier AI/ML venues. - Experience with large language model training, fine-tuning, or evaluation. - Familiarity with retrieval-augmented generation, agentic systems, or multimodal architectures. - Exposure to responsible AI, model evaluation, and alignment practices. - Experience contributing to open-source ML projects. 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. 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.

• Work with industry-leading technologies like Kafka, Flink, Redis, ElasticSearch and Cassandra and LLMs. • Develop, maintain, and enhance the capabilities of distributed cloud services. • Keeping services up and running in a healthy state. • Work closely with other internal engineering teams to integrate new capabilities into our Falcon platform

Role Description We are currently searching for a SDET: - Drive quality improvements end to end by applying innovative thinking and taking full ownership of the testing lifecycle. - Design and code robust automation frameworks from scratch. - Test agentic AI applications, focusing on workflow accuracy, tool usage, and failure handling. - Mentor team members and contribute to quality engineering best practices across the organization. Qualifications - Strong automation engineering background with hands-on framework design and coding. - Hands-on expertise in Playwright for UI and end-to-end automation. - Proven experience testing APIs, integration flows, and CI/CD quality gates. - Experience testing agentic AI applications, including workflow accuracy, tool usage, and failure handling. - Strong programming skills in Java, Python, or similar languages for automation. - Ownership mindset, innovative thinking, and ability to drive quality improvements end to end. Requirements - Hands-on expertise in Playwright for UI and end-to-end automation. - Proven experience testing APIs, integration flows, and CI/CD quality gates. - Experience testing agentic AI applications, including workflow accuracy, tool usage, and failure handling. - Strong programming skills in Java, Python, or similar languages for automation. - Ownership mindset, innovative thinking, and ability to drive quality improvements end to end. Benefits - Flexibility to support your lifestyle with remote work options.

Role Description We are seeking an experienced Senior Investment Research & Capital Markets Subject Matter Expert to support the development, evaluation, and improvement of advanced Artificial Intelligence (AI) models. This is not a traditional Investment Banking position. Instead, you will apply your real-world expertise to evaluate complex AI-generated financial analyses, validate technical reasoning, identify inaccuracies, and help improve Large Language Models (LLMs) used within the finance industry. We are looking for professionals who are recognized as experts within their field—individuals capable of evaluating financial reasoning with the same rigor expected in investment banking, corporate finance, transaction advisory, and institutional finance environments. Domain Expertise - Equity Research - Fixed Income Research - Credit Research - Investment Research - Asset Management - Portfolio Management - Buy-Side - Sell-Side - Capital Markets Strong candidates typically have practical experience with: - Published research - Managed investment portfolios - Presented to investment committees Key Responsibilities - Evaluate AI-generated financial analyses for technical accuracy, completeness, and quality of reasoning. - Identify factual inaccuracies, unsupported assumptions, logical inconsistencies, and calculation errors. - Review financial models, valuation methodologies, and investment analyses produced by AI. - Create, review, and refine finance-related prompts, benchmark responses, and evaluation datasets. - Apply detailed annotation guidelines consistently while maintaining exceptional quality standards. - Provide structured, actionable feedback that improves AI model performance. - Collaborate with Project Managers, Quality Assurance teams, and AI Researchers to improve evaluation methodologies. - Maintain productivity and quality expectations while working independently in a remote environment. Qualifications - Significant practical experience in Investment Banking, Corporate Finance, or Transaction Advisory. - Strong knowledge of U.S. financial markets and corporate finance principles. - Exceptional analytical and critical thinking skills. - Advanced financial modeling and valuation capabilities. - Excellent written English communication skills. - Ability to independently evaluate complex financial analyses and articulate technical feedback. - Strong attention to detail and commitment to quality. Preferred Qualifications - Professional Certifications - CFA (Completed or Candidate) - CPA - MBA (Finance) - Chartered Accountant (CA) Professional Background - Investment Banking - Big Four Transaction Advisory - Valuation Advisory - Private Equity - Venture Capital - Corporate Development - Strategic Finance Financial Platforms - Bloomberg Terminal - Capital IQ - FactSet - Refinitiv - PitchBook AI Experience - Previous experience with any of the following is highly desirable: - AI Model Evaluation - Reinforcement Learning from Human Feedback (RLHF) - Prompt Engineering - AI Annotation - Large Language Model (LLM) Evaluation - AI Quality Assurance - Benchmark Dataset Development Candidates without prior AI evaluation experience may still be considered if they possess exceptional domain expertise and strong analytical reasoning. U.S. Market Knowledge - SEC Filings - Public Equities - Financial Statements - Valuation Methodologies - Corporate Earnings - Macroeconomic Indicators - Investment Analysis - Capital Markets - Financial Ratios - Portfolio Concepts - Market Trends What Makes a Strong Candidate - Successful candidates are often professionals who have: - Led complex financial analyses or valuation engagements. - Reviewed or approved the work of other finance professionals. - Supported or led high-profile transactions. - Presented recommendations to executive leadership, investment committees, or clients. - Built financial models used in strategic business decisions. - Applied expert judgment to evaluate complex financial scenarios. Trial Gig (Required) As part of the selection process, all shortlisted candidates must successfully complete a Trial Gig designed to evaluate technical finance expertise, analytical reasoning, written communication, attention to detail, and the ability to assess AI-generated financial responses. Please note: - Successful completion of the Trial Gig is required before joining the production project. - Candidates who meet the required quality standards will receive an offer to join the project and will be compensated for successfully completing the Trial Gig. - Candidates who do not meet the required quality standards will not move forward on this project and will not receive compensation for the Trial Gig. - Strong candidates who are not selected may remain in our talent network and be considered for future AI evaluation projects that better align with their expertise.