出海雷达

机器学习研究工程师

Machine Learning Research Engineer

AI开发工程限定地区(需当地身份)
公司Bright Vision Technologies
薪资$100,000 - $150,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间14 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

机器学习研究工程师 - 远程办公

Bright Vision Technologies 是一家技术咨询和软件开发公司,为美国各地提供云计算、人工智能、数据和企业解决方案。
这是加入一家知名且受人尊敬的组织的绝佳机会,提供巨大的职业发展潜力。

职位名称:机器学习研究工程师
地点:100% 远程(美国)
职位类型:全职,直接 W2
薪资范围:每年 100,000–150,000 美元
所需经验:6 年以上

赞助:美国公民、绿卡持有者、EAD 持有者以及 H-1B 转换候选人欢迎申请。我们无法为该职位的新 H-1B 签证申请提供赞助。

职位概述
我们正在寻找一名 AI 研究工程师,将前沿的应用研究与生产工程相结合,设计并交付解决高影响力业务问题的先进机器学习系统。该角色融合了科学严谨性和实际软件工程,要求对现代 ML 和深度学习技术有深入理解,同时具备构建稳健、可扩展且具有良好监控功能的生产流程的能力。理想的候选人紧跟快速发展的 AI 研究动态,能够批判性地评估新技术在现实场景中的适用性,并能够在从问题定义和实验到部署和持续改进的整个生命周期中自如操作。

主要职责
· 在自然语言、视觉、推荐和结构化数据领域设计、原型设计和评估应用 AI 解决方案。

  • 将模糊的业务问题转化为明确的 ML 表述,包含清晰的成功指标和评估策略。
  • 跟踪深度学习、大语言模型及相邻领域的最新研究成果,并评估其在内部用例中的适用性。
  • 实现严格的实验工作流程,包括基线测试、消融实验和统计上合理的评估方法。
  • 使用现代 ML 框架和编排工具构建高质量的训练和推理流程。
  • 与 ML 平台工程师合作,确保计算、存储和加速器资源的高效使用。
  • 根据生产需求优化模型的准确性、延迟、吞吐量和成本。
  • 开发用于数据集构建、标注、验证以及数据质量持续监控的工具。
  • 与产品、设计和
查看英文原文

Machine Learning Research Engineer - Remote

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: Machine Learning Research Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$150,000 Annually
Experience Required: 6+ years

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary
We are seeking an AI Research 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.

Required 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  or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at .
Bright Vision Technologies is an Equal Opportunity Employer.
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.
Originally posted on Himalayas

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