---
title: 'Forward Deployed AI Engineer (Post-Sales) at DatologyAI'
canonical: 'https://feeny.ai/job/forward-deployed-ai-engineer-post-sales-datologyai-san-mateo-exyc2z5wjfcx'
type: 'job'
last_seen: '2026-09-05'
---

# Forward Deployed AI Engineer (Post-Sales) at DatologyAI

- **Company:** DatologyAI
- **Location:** San Mateo, CA
- **Employment:** full-time
- **Posted:** 2026-05-27
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.ashbyhq.com/datologyai/3c86dc94-349e-46c0-ae91-029f904410a0

## Job description

## ABOUT THE COMPANY

Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.

At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy).

We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.

This role is based in San Mateo, CA. We are in office 4 days a week.

## ABOUT THE ROLE

We are looking for a highly technical, customer-obsessed Forward Deployed AI Engineer (Post Sales) to guide customers through deploying, operating, and adopting DatologyAI’s platform in complex on-prem or hybrid environments. You will become the trusted technical advisor for our most strategic customers, partnering closely with Sales, Research, and Engineering to drive successful deployments and long-term customer value. You'll bridge the gap between our core platform capabilities and the unique requirements of each customer's environment.

This role is ideal for someone who thrives in ambiguity, enjoys solving challenging distributed systems problems, and wants to build both deep relationships and scalable solutions within a fast-moving startup.

## WHAT YOU’LL WORK ON

- Lead customers through onboarding, deployment, and production rollout of DatologyAI’s platform while serving as the technical owner for assigned accounts—driving architecture, execution, long-term adoption, and tailored technical success plans.
- Partner cross-functionally with Sales, Engineering, and Research to translate use-case requirements into actionable technical strategies, support early trials, relay customer feedback, and help shape roadmap priorities.
- Guide customers in designing scalable, secure workflows across compute, storage, networking, and distributed systems, providing ongoing reporting on deployment progress, workload health, usage metrics, and executive-level updates.
- Adapt and optimize DatologyAI’s platform across AWS, GCP, Azure, and on-prem Kubernetes environments, handling provider-specific APIs, storage systems, networking configurations, and compute orchestration—including tuning performance for network topology, storage tiering, and resource allocation in each environment.

## ABOUT YOU

- 5+ years of experience in technical roles involving solution architecture, customer engineering, consulting, or technical program delivery.
- Strong background in distributed systems, data infrastructure, and/or on-prem or hybrid compute environments.
- Experience working with ML/AI workflows, designing or deploying systems involving Kubernetes, networking, data pipelines, or large-scale backend infrastructure.
- Proficiency in Python, SQL, or similar languages, with the ability to contribute to technical conversations and debug customer issues end-to-end.
- Experience leading complex technical projects with multiple stakeholders—translating business needs into clear architecture and execution plans.
- Deep hands-on experience with multiple cloud platforms (AWS, GCP, Azure) including their compute, storage, networking, and IAM services.
- Proven track record of adapting complex distributed systems to run across different infrastructure environments.
- Expertise in infrastructure-as-code and configuration management for multi-environment deployments.
- Required to travel to customer sites as needed to support critical deployments and customer engagements.

## COMPENSATION

At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $230,000 to $300,000.

- Starting pay is based on job-related skills, experience, qualifications, and interview performance.

Benefits:

- 100% covered health benefits (medical, vision, and dental).
- 401(k) plan with a generous 4% company match.
- Unlimited PTO policy
- Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
- Annual $2,000 wellness stipend.
- Annual $1,000 learning and development stipend.
- Daily lunches and snacks are provided in our office!
- Relocation assistance for employees moving to the Bay Area.

## About DatologyAI

## Company Overview
- **One-liner**: DatologyAI provides an automated platform that curates training data for deep learning models, helping companies train better AI models faster and more cost-effectively.
- **Entity Type**: Private (Series A)
- **Headquarters**: Redwood City, California, United States
- **Founded**: 2023
- **Founders**: Ari Morcos (CEO), Bogdan Gaza (CTO), Matthew Leavitt

## Core Business
- **Primary industry/industries**: Artificial intelligence, Machine learning infrastructure, Data curation
- **Target customers**: B2B — Enterprises and AI teams training large-scale deep learning models across verticals
- **Mission or purpose statement**: "Democratize AI data curation, allowing every company to easily train its own custom model on the right data without needing to invest massive resources." [datologyai.com](https://www.datologyai.com/about)

## Products & Services
- **DatologyAI Platform**: A fully automated, scalable data curation platform that identifies redundant, noisy, or harmful data points in training datasets. It integrates with existing infrastructure (from blob storage to dataloader), is modality-agnostic (works for text, images, etc.), and requires no labels. The goal is to optimize training efficiency, maximize model performance, and reduce compute costs. [datologyai.com](https://www.datologyai.com/about)

## Market Standing
- **Valuation/Market Cap**: Not publicly available
- **Key Metric**: Total funding of $57.65M [cbinsights.com](https://www.cbinsights.com/company/datologyai)
- **Notable Investors/Partners**: M12 (Microsoft’s venture fund), Amplify Partners, Amazon Alexa Fund [datologyai.com](https://www.datologyai.com/about)
- **Growth Signals**: Founded in 2023 and already raised $57.65M (including a $46M Series A in 2024); backed by top-tier investors; founded by researchers with backgrounds at DeepMind, Meta AI (FAIR), and MosaicML (acquired by Databricks); cutting-edge research (80% novel and unpublished) directly powers the product.

## Competitive Advantages
- **Research-driven product**: The platform is built on frontier research in data curation for deep learning, with the team publishing novel techniques at top conferences (NeurIPS, ICLR).
- **Modality-agnostic & label-free**: Works across data types and doesn’t require labeled data, making it applicable to a wide range of use cases.
- **Deep technical team**: Founders bring expertise from leading AI labs (DeepMind, Meta AI, MosaicML) and large-scale infrastructure experience (Amazon, Twitter).
- **Customer-obsessed and scalable**: Designed to be easy to implement and generalize across models, directly reducing compute costs for customers.

## Strategic Focus
- **Product & research**: Continue to push the boundaries of data curation research and deploy it directly into the product to improve model efficiency and capability.
- **Customer success**: Deeply focus on customer problems and goals to drive adoption and success.
- **Scaling the team**: Actively hiring across engineering, research, sales, and product roles to grow the organization.

## Why Work Here
- **Impactful mission**: Solve the "biggest problem in AI model training" — data quality — with research that has real-world impact.
- **World-class team**: Work alongside researchers and engineers from DeepMind, Meta AI, and MosaicML.
- **Culture of research**: Engineering and research are deeply intertwined; ideas are deployed into production, not just published.
- **In-office culture**: HQ in Redwood City, CA, with a strong in-office expectation ("In-Office" listed for all roles on Built In). [builtin.com](https://builtin.com/company/datologyai)
- **Benefits**: 100% covered health benefits (medical, vision, dental), 401(k) with 4% match, unlimited PTO, $2,000 annual wellness stipend, $1,000 annual L&D stipend, daily lunch/snacks, dinner for late work, relocation assistance. [datologyai.com](https://www.datologyai.com/careers)
- **Fast-paced, high-growth environment**: A chance to grow fast and make a significant impact at a well-funded startup.

## Sources
1. [DatologyAI About Page](https://www.datologyai.com/about)
2. [DatologyAI Careers Page](https://www.datologyai.com/careers)
3. [Built In Company Profile](https://builtin.com/company/datologyai)
4. [CB Insights Company Profile](https://www.cbinsights.com/company/datologyai)
5. [LinkedIn Company Page](https://www.linkedin.com/company/datologyai)

## Other roles at DatologyAI

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