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

**Company:** [Datology AI](https://hotfix.jobs/companies/datology-ai)
**Location:** Redwood City, CA
**Role:** Sales Engineering
**Salary:** $230k – $300k/yr
**Experience:** 4+ years
**Skills:** Python, PyTorch, Hugging Face, Spark, Ray, AWS, GCP, Azure, Docker, Kubernetes
**Posted:** 2026-01-09

> Leads pre-sales PoCs for AI/ML data curation platform, partnering with customer ML teams to design evaluations, demonstrate training efficiency gains, and communicate results to technical and executive audiences. Requires 4+ years in ML platforms with hands-on training and evaluation expertise.

## Job Description

## 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.
- 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

- Salary ranges from **$230,000 to $300,000 OTE**.
- **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 provided in office.
- Relocation assistance for employees moving to the Bay Area.

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