---
title: 'Solutions Engineer (AI/ML, Pre-Sales) at DatologyAI'
canonical: 'https://feeny.ai/job/solutions-engineer-ai-ml-pre-sales-datologyai-san-mateo-8nw2w7atdymv'
type: 'job'
last_seen: '2026-10-17'
---

# Solutions Engineer (AI/ML, Pre-Sales) at DatologyAI

- **Company:** DatologyAI
- **Location:** San Mateo, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-01-09
- **Last confirmed live:** 2026-10-17
- **Apply:** https://jobs.ashbyhq.com/datologyai/9a0a1eb0-1b92-4074-9385-01599929cc03

## 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 Solutions Engineer with deep ML and AI platform experience to support customers in a pre-sales role. In this role, you will partner closely with our most strategic prospects to deeply understand their data curation needs, technical constraints, and business goals, and to design scalable solutions that demonstrate the impact of DatologyAI’s platform. This role requires strong hands-on understanding of modern LLM/VLM training and evaluation. You will work directly with customer ML teams to design PoCs that connect data curation decisions to measurable outcomes in model quality, training efficiency, and downstream performance—across the full lifecycle of training (pre-training, mid-training, and post-training), and with rigorous evaluation plans and reporting.

## What You’ll Work On

- Embed deeply with strategic customers to understand their data curation needs, business challenges, and technical requirements in detail.
- Lead end-to-end customer PoCs that connect data curation, training behavior, evaluation outcomes, including dataset analysis, training plan design, and results interpretation.
- Partner with customer ML teams to map data & curation strategy
- Design and execute evaluation plans for base and post-trained models, selecting appropriate benchmarks/metrics, and running model evaluations
- Produce customer-ready evaluation reports: methodology, metrics, baselines, ablations (e.g., curated vs raw), conclusions, and recommended next steps for productionization.
- Communicate technical results to both ML experts and exec stakeholders, including tradeoffs in compute, latency, and deployment cost.
- Collaborate closely with GTM, Engineering, and Research teams to ensure seamless customer experiences, deliver compelling demos, align on requirements, and bring customer insights into actionable model training and product strategies.
- Provide technical guidance, training, and clear documentation to ensure prospects can confidently assess the solution.

## About You

- 4+ years of experience in software, ML platform, solutions, or customer engineering roles, with significant experience driving technical pre-sales engagements and PoCs.
- Strong practical expertise in ML model training, including how models are trained and improved across pre-training, domain-specific mid-training, and post-training, such as supervised fine-tuning and reinforcement learning.
- Demonstrated ability to design, run, and interpret model evaluations for base and post-trained models: choosing metrics/benchmarks, building or using evaluation harnesses, analyzing results, and presenting findings clearly with customers.
- Examples of the kinds of practical deep learning questions you might have to answer for customers:
- What’s the difference between MMLU, MMMU, and MMMLU?
- Is SWE-Bench a useful eval for base models?
- What’s a standard context window for pretraining, and what are the costs and benefits of changing it?
- What’s the difference between CPT and midtraining?
- Can we just compare your data to Qwen3?
- Will your data work with our model architecture?
- Strong programming skills in Python (or equivalent); able to prototype quickly and iterate with customers.
- Experience with data processing / distributed systems (e.g., Spark, Ray, data lakes/warehouses) and comfort working with large-scale datasets.
- Familiarity with modern ML infrastructure: PyTorch/Hugging Face ecosystems, distributed training concepts, and deployment environments across cloud/on-prem/hybrid.
- Familiarity with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Strong communication skills, with the ability to translate complex ML and systems topics for diverse audiences.
- Required to travel to customer sites as needed to support pre-sales 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 OTE.

- 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

- [Founding Operations Manager, UK](https://feeny.ai/job/founding-operations-manager-uk-datologyai-london-mpavmkm0dx4z) — London, United Kingdom
- [Software Engineer, Infrastructure](https://feeny.ai/job/software-engineer-infrastructure-datologyai-san-mateo-27yxqv5jp2gv) — San Mateo, CA
- [Research Scientist, Post-Training](https://feeny.ai/job/research-scientist-post-training-datologyai-san-mateo-b9tsptwy59j9) — San Mateo, CA
- [AI Developer Experience & Media Lead](https://feeny.ai/job/ai-developer-experience-media-lead-datologyai-san-mateo-pf7jfn1t6ad9) — San Mateo, CA
- [Research Engineer](https://feeny.ai/job/research-engineer-datologyai-san-mateo-5cps4zyfezck) — San Mateo, CA
- [Forward Deployed AI Engineer (Post-Sales)](https://feeny.ai/job/forward-deployed-ai-engineer-post-sales-datologyai-san-mateo-exyc2z5wjfcx) — San Mateo, CA
- [Research Scientist](https://feeny.ai/job/research-scientist-datologyai-san-mateo-01jmy0y7mzym) — San Mateo, CA
- [Product Manager](https://feeny.ai/job/product-manager-datologyai-san-mateo-f6ef705z2p47) — San Mateo, CA
- [Software Engineer, Front-end](https://feeny.ai/job/software-engineer-front-end-datologyai-san-mateo-r9gh13jqy1rt) — San Mateo, CA
- [Software Engineer, Cloud Infrastructure](https://feeny.ai/job/software-engineer-cloud-infrastructure-datologyai-san-mateo-48ybp4z0yc7x) — San Mateo, CA