914 roles across 160 companies — filter by region or category.
Showing 50 of 101 matching positions (1–50)
Clear filtersTrain, evaluate and release open models, and maintain the libraries the community builds on.
Model merchant lifecycles and turn the findings into product and pricing decisions.
Build the pipelines behind product analytics for services used by a very large share of the web.
Build semantic and hybrid search features on top of the Elastic Stack for enterprise customers.
Train, evaluate and serve models that power Airbyte's open-source projects at production scale.
Build the ingestion, storage and query layers that every team uses to reason about Airbyte's open-source projects.
Own the lakehouse and streaming infrastructure underneath Amplitude's analytics platform, with an eye on cost and freshness.
Own the modelling loop behind Automattic's open-source projects — features, training pipelines, offline evaluation and online experiments.
Own the lakehouse and streaming infrastructure underneath BrowserStack's developer platform, with an eye on cost and freshness.
Own the modelling loop behind Buffer's product suite — features, training pipelines, offline evaluation and online experiments.
Train, evaluate and serve models that power Cal.com's open-source projects at production scale.
Build the ingestion, storage and query layers that every team uses to reason about Canonical's open-source projects.
Investigate training, alignment and evaluation methods that make the models behind CircleCI's developer platform more useful.
Design and run large-scale training experiments, then turn the findings into production model releases.
Optimise inference throughput and cost for the models running behind ClickHouse's data platform.
Model warehouse data into tested, documented datasets the whole company trusts when analysing Close's product suite.
Own the modelling loop behind Cohere's AI products — features, training pipelines, offline evaluation and online experiments.
Design and run large-scale training experiments, then turn the findings into production model releases.
Model warehouse data into tested, documented datasets the whole company trusts when analysing Coinbase's financial platform.
Own the lakehouse and streaming infrastructure underneath Coinbase's financial platform, with an eye on cost and freshness.
Design and run large-scale training experiments, then turn the findings into production model releases.
Own the lakehouse and streaming infrastructure underneath CrowdStrike's security platform, with an eye on cost and freshness.
Optimise inference throughput and cost for the models running behind dbt Labs's data platform.
Build the ingestion, storage and query layers that every team uses to reason about DigitalOcean's product suite.
Own the lakehouse and streaming infrastructure underneath Drata's security platform, with an eye on cost and freshness.
Run experiments that push the model capabilities behind Elastic's developer platform, and publish or ship what works.
Train, evaluate and serve models that power Elastic's developer platform at production scale.
Optimise inference throughput and cost for the models running behind ElevenLabs's AI products.
Run experiments that push the model capabilities behind Fivetran's data platform, and publish or ship what works.
Probe model behaviour for failure modes and build the evaluations that gate releases across Fivetran's data platform.
Train, evaluate and serve models that power Fly.io's developer platform at production scale.
Own the lakehouse and streaming infrastructure underneath Fly.io's developer platform, with an eye on cost and freshness.
Own the modelling loop behind GitHub's developer platform — features, training pipelines, offline evaluation and online experiments.
Design red-teaming and evaluation methodology for the models behind GitHub's developer platform, and turn results into mitigations.
Probe model behaviour for failure modes and build the evaluations that gate releases across GitLab's developer platform.
Build the ingestion, storage and query layers that every team uses to reason about Grafana Labs's developer platform.
Model warehouse data into tested, documented datasets the whole company trusts when analysing HashiCorp's developer platform.
Own the transformation layer and semantic definitions behind reporting on Hotjar's analytics platform.
Train, evaluate and serve models that power Linear's developer platform at production scale.
Own the lakehouse and streaming infrastructure underneath Miro's product suite, with an eye on cost and freshness.
Model warehouse data into tested, documented datasets the whole company trusts when analysing Miro's product suite.
Train, evaluate and serve models that power Modal's developer platform at production scale.
Own the transformation layer and semantic definitions behind reporting on Modal's developer platform.
Own the modelling loop behind MongoDB's developer platform — features, training pipelines, offline evaluation and online experiments.
Own the lakehouse and streaming infrastructure underneath 1Password's security platform, with an eye on cost and freshness.
Train, evaluate and serve models that power 1Password's security platform at production scale.
Run experiments that push the model capabilities behind Pinecone's developer platform, and publish or ship what works.
Design red-teaming and evaluation methodology for the models behind PostHog's analytics platform, and turn results into mitigations.
Own the lakehouse and streaming infrastructure underneath PostHog's analytics platform, with an eye on cost and freshness.
Own the modelling loop behind Remote's employment platform — features, training pipelines, offline evaluation and online experiments.
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