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Agentio

Research Engineer, Applied AI

Posted An Hour Ago
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In-Office
New York, NY, USA
195K-400K Annually
Entry level
In-Office
New York, NY, USA
195K-400K Annually
Entry level
Conduct applied AI and machine learning research spanning multimodal intelligence, recommendation, ranking, prediction, foundation models, agents, and decision-making. Define research problems, evaluate and develop models using proprietary data, run rigorous experiments, create training signals and evaluations, and transition successful approaches into production systems. Collaborate with engineering and product teams while shaping the company’s research agenda and technical standards.
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About Agentio

Agentio builds AI-native infrastructure for creator advertising. Our platform uses AI to turn creative and performance signals into campaign strategies, match brands with creators, recommend sponsorship prices, and review videos against brand requirements.

Each campaign generates feedback: how brands respond to our recommendations, which offers creators accept, and how the resulting content performs. We build self improving loops that learn from these behaviors and outcomes to better understand preferences, predict performance, and improve campaign decisions.

We're looking for a Research Engineer to advance that work through applied AI and ML research, developing models that improve the platform's predictions and automate more of the decisions behind creator advertising.

The work spans research and production. You'll evaluate methods from academia and industry, adapt and train models on Agentio's proprietary data, develop new approaches when existing methods fall short, and work with engineering and product to ship them.

What You'll Work On

Multimodal intelligence. Build systems that understand creators, brands, briefs, and content across video, audio, image, and text.

Ranking, recommendation, and prediction. Develop models that predict creator-brand fit and campaign outcomes and make better decisions from sparse, heterogeneous feedback.

Foundation models and agents. Apply LLMs and multimodal models to campaign planning, discovery, creative understanding, execution, and optimization. Use Agentio's proprietary data for prompting, retrieval, fine-tuning, post-training, and, where it makes sense, specialized model training.

Learning and decision-making. Turn campaign data into training signals, evals, and learning loops while tackling problems in optimization, exploration, measurement, and marketplace dynamics.

Part of the role is deciding which advances in AI and ML are useful for Agentio and where new methods are needed.

What You'll Do
  • Own research problems from problem definition and experimentation through production.

  • Evaluate relevant AI and ML methods against Agentio's data, build rigorous experiments and evaluations, and measure performance in production.

  • Develop models, algorithms, training approaches, or datasets when existing techniques aren't sufficient. Work with engineering and product to ship successful approaches.

  • Help set Agentio's research agenda and technical standards for applied ML.

Who We're Looking For

We're looking for someone with strong research judgment who also wants to build production systems.

  • Demonstrated experience conducting applied ML research, with original work shown through production ML systems, publications, open-source research, or comparable contributions. A PhD or advanced degree in ML, AI, computer science, statistics, or a related field is useful but not required.

  • Depth in one or more areas such as foundation models, multimodal learning, recommendation and ranking, representation learning, reinforcement learning and decision-making, causal inference, optimization, or adjacent fields.

  • Ability to turn ambiguous product problems into tractable research questions, run rigorous experiments, and translate successful approaches into production systems.

  • Strong engineering skills and experience taking ML work beyond prototypes.

  • Strong knowledge of current AI research and the judgment to determine which methods are useful in practice.

What You'll Get
  • The opportunity to build a first-of-its kind business as an early team-member and make a meaningful impact in the way brands share their stories and creators live off their work.

  • Crash-course in what it takes to scale a start-up with first-hand exposure to the different foundational business drivers and needs.

  • The chance to work with an exceptional team and help build our engineering culture

  • A collaborative, transparent, and engaging work environment.

 
Benefits & Perks
  • Flexible PTO – Take the time you need to recharge

  • Comprehensive Health Coverage – Top medical plan through Aetna

  • Dental & Vision Plans – Protect your smile and your sight with coverage from Guardian

  • 401(k) Retirement Plan – Invest in your future while you build your career

  • $100 Monthly Lifestyle Credit – Use it to shop with our amazing Agentio Brand Partners

  • Daily lunches and snacks in the office to keep you at your best

  • Dinner provided Monday - Thursday

  • Fully subsidized gold tier access on Wellhub (Includes LifeTime, Barry's, Solidcore, Headspace, etc)

  • Gym in the building! – Your workout, right downstairs

Agentio is an equal-opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

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Agentio New York, New York, USA Office

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Located in the heart of NoMad, our office sits at the center of one of NYC’s most dynamic neighborhoods. Surrounded by top restaurants, coffee spots, and close to Madison Square Park, it’s a hub for tech, startups, and creative energy. With easy access to multiple subway lines, it’s as convenient as

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