Description review
Lucia | Director of Corp Dev · Product
Lucia · Remote · back to the listing
HR standards
51/100
needs work
Title ↔ description
22/100
poor
Reads as
Machine Learning Engineer
92% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
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What the listing never says
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Marketing Associate · MLOps Engineer| Remote (NYC / SEA / global overlap) | $140K–$200K + meaningful equity
Distribution is one of the last durable moats left; models are commoditizing, but knowing how attention and demand actually move through a system still compounds. That's what we're building: a growth control plane that turns distribution into something you can model and act on with certainty. Get this right and the outcome isn't in question.
We're hiring across three roles:
Director, Corporate Development: own strategic partnerships, fundraising support, and M&A/inorganic growth. For someone who can operate at the intersection of deal-making and narrative, and help steer where this company goes next.
Product Marketing Associate: translate a technically deep product into sharp positioning and demand. For someone who can make causal modeling and world models land with real buyers. Experience with working with social media and influencers, Reddit strongly preferred. Data Science Background heavily preferred.
MLOps Engineer: own the infra behind our modeling; production pipelines and serving for causal graph inference, state space models, and world models (JEPA-I, JEPA-II style). Creating certainty in distribution, in production, not just in notebooks. Stack: Python, PyTorch, some Rust; GCP; Ray for distributed training.
Interview process: intro call, screen, virtual onsite, decision.
Apply: with an email with your CV to [email protected] mention HN SEPT2026 in subject
Distribution is one of the last durable moats left; models are commoditizing, but knowing how attention and demand actually move through a system still compounds. That's what we're building: a growth control plane that turns distribution into something you can model and act on with certainty. Get this right and the outcome isn't in question.
We're hiring across three roles:
Director, Corporate Development: own strategic partnerships, fundraising support, and M&A/inorganic growth. For someone who can operate at the intersection of deal-making and narrative, and help steer where this company goes next.
Product Marketing Associate: translate a technically deep product into sharp positioning and demand. For someone who can make causal modeling and world models land with real buyers. Experience with working with social media and influencers, Reddit strongly preferred. Data Science Background heavily preferred.
MLOps Engineer: own the infra behind our modeling; production pipelines and serving for causal graph inference, state space models, and world models (JEPA-I, JEPA-II style). Creating certainty in distribution, in production, not just in notebooks. Stack: Python, PyTorch, some Rust; GCP; Ray for distributed training.
Interview process: intro call, screen, virtual onsite, decision.
Apply: with an email with your CV to [email protected] mention HN SEPT2026 in subject