Parallel Web Systems

Parallel is a web infrastructure company building the web for AIs. Our products enable leading businesses to create AI agents with programmatic access to the web. We are seeking a Deployed Engineer to join our team, working closely with customers to help them maximize the value of our API and scale their operations. This role requires a deep understanding of customer products, use-cases, and our API, positioning you as a power user.

$150k - $300k

Parallel is a web infrastructure company building the web for AIs. Our products enable leading businesses to create AI agents with programmatic access to the web. We are seeking researchers to answer the question of how to train and scale a model that can serve a web index. You will have deep intuition on modern models and training, and enjoy exploring how search, recommendations, and transformer models can converge. Your research will be applied to products and systems used by millions.

$150k - $300k

You will own the training pipeline behind the models that power both Parallel’s search stack and Parallel’s agents. On the search side, this involves the rankers, classifiers, and query models that surface the right information. On the agent side, this means the models that help our agents plan, reason, and execute high-value tasks over web data. You will build the path from real product usage to high-quality training data, fine-tune and evaluate these models rigorously, and ship them safely to traffic used by millions. You have a deep intuition on modern models and training, including transformer fine-tuning, data curation, and the craft of label quality, and you care about your research being applied to product and systems that millions use.

$150k - $300k

Parallel is seeking a Member of Technical Staff focused on Retrieval & Indexing to build and operate the systems powering our large-scale full-text index over the web. This role involves the entire lifecycle, from deciding corpus content and building searchable structures to developing signals and models for source quality and freshness, and efficiently serving queries. You will proactively identify and address architectural bottlenecks to ensure our systems scale with increasing demand.

$150k - $300k

Parallel is seeking a researcher who thinks like an engineer, or an engineer who thinks like a researcher, to join our team. You will design and train the models that power Parallel's APIs, focusing on the intelligence layer that helps AI agents find exactly what they need from the open web. This role involves tackling research problems at hyperscale, such as training embedding models that capture semantic intent, balancing model expressiveness with sub-second retrieval latency, and maintaining index freshness. You will be building information retrieval systems reimagined for the LLM era, combining classical IR techniques with modern deep learning at a scale that demands new solutions.

$150k - $300k