Solutions Engineer (AI/ML, Pre-Sales)

DatologyAI • Redwood City, CA

2d • $230,000 - $300,000 • Onsite

About The Position

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.

Requirements

• 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.
• 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.

Responsibilities

• 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.

Benefits

• 100% covered health benefits (medical, vision, and dental).
• 401(k) plan with a generous 4% company match.
• Unlimited PTO policy
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 11-50 employees