{"id":3135541,"url":"https://alion.io/job/hirevouch-applied-research-engineer","title":"Applied Research Engineer","company":{"id":4415880,"name":"hireVouch","domain":"hirevouch.com","url":"https://alion.io/company/hirevouch","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"CATS","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":160000,"max_usd":310000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":477},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"DPO","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLHF","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-23T05:34:23Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-24T04:36:46Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"We're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.\nAbout Us\nWe're the only company offering three integrated solutions for frontier AI development:\nEnterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale\nFrontier Data Labeling Service: Specialized data labeling through Aligner, leveraging subject matter experts for next-generation AI models\nExpert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling\nWhy Join Us\nHigh-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.\nTechnical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.\nInnovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.\nContinuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.\nClear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.\nRole Overview\nAs an Applied Research Engineer, you will be at the forefront of developing cutting-edge systems and methods to create, analyze, and leverage high-quality human-in-the-loop data for frontier model developers. Your role will involve designing and implementing advanced systems that align human feedback into AI training processes, such as Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), etc. You will also work on innovative techniques to measure and improve human data quality, and develop AI-assisted tools to enhance the data labeling process. Your expertise in machine learning, frontier model training, and advanced human data alignment techniques will be crucial in pushing the boundaries of AI capabilities and delivering state-of-the-art solutions to meet the evolving needs of our customers.\nYour Impact\nAdvance the field of AI alignment by developing cutting-edge methods, such as RLHF and novel approaches, that ensure AI systems reflect human preferences more accurately.\nImprove the quality of human-in-the-loop data by designing and deploying rigorous measurement and enhancement systems, leading to more reliable AI training.\nIncrease efficiency and effectiveness in AI-assisted data labeling by creating tools that leverage active learning and adaptive sampling, reducing manual effort while improving accuracy.\nShape the next generation of AI models by investigating how different types of human feedback (e.g., demonstrations, preferences, critiques) impact model performance and alignment.\nOptimize human feedback collection by developing novel algorithms that enhance how AI learns from human input, improving model adaptability and responsiveness.\nBridge research and real-world application by integrating breakthroughs into our product suite, making human-AI alignment techniques scalable and impactful for users.\nDrive industry innovation by engaging with customers and the broader AI community to understand evolving data needs and share best practices for training frontier models.\nContribute to the AI research ecosystem by publishing in top-tier journals, presenting at leading conferences, and influencing the future of human-centric AI.\nStay ahead of AI advancements by continuously exploring new frontiers in human-AI collaboration, human data quality, and AI alignment, keeping us at the cutting edge.\nEstablish us as a thought leader in AI by creating technical documentation, blog posts, and educational content that shape the industry's approach to human-centric AI development.\nWhat You Bring\nA strong foundation in AI and machine learning, backed by a Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related field.\nProven experience (3+ years) in solving complex ML challenges and delivering impactful solutions that improve real-world AI applications.\nExpertise in designing and implementing data quality measurement and refinement systems that directly enhance model performance and reliability.\nA deep understanding of frontier AI models-such as large language models and multimodal models-and the human data strategies needed to optimize them.\nProficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow to prototype and develop cutting-edge solutions.\nA track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community.\nThe ability to bridge research and application by interpreting new findings and rapidly translating them into functional prototypes.\nStrong analytical and problem-solving skills that enable you to tackle ambiguous AI challenges with structured, data-driven approaches.\nExceptional communication and collaboration skills, allowing you to work effectively across multidisciplinary teams and with external stakeholders.","description_format":"text","description_chars":5551,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-23T05:34:23Z"}],"visa":[],"liveness":{"score":54,"band":"ok","label":"Likely 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