Page 1
Loading more openings…
You've reached the end of the list.
Solutions Engineer (AI/ML, Pre-Sales)
DatologyAI · Redwood City, California, USA
Pay
$230k–300k
Setting
On-site
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 Redwood City, 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.
Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.
Forward Deployed AI Engineer (Post-Sales)
DatologyAI · Redwood City, California, USA
Pay
$230k–300k
Setting
On-site
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 Redwood City, 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.
Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.
Select a role
The full posting opens here — pay, setting and the full description, without leaving the list.