{"id":468130,"url":"https://alion.io/job/datologyai-solutions-engineer-aiml-pre-sales","title":"Solutions Engineer (AI/ML, Pre-Sales)","company":{"id":9100,"name":"DatologyAI","domain":"datologyai.com","url":"https://alion.io/company/datologyai","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":60,"open_postings":12,"ghost_share":0.667,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":48,"computed_at":"2026-10-19T05:45:15Z"}},"role":"Solutions","role_family":"Solutions","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Mateo, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":230000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Post-training","optional":false},{"name":"Pre-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Ray","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"SFT","optional":false},{"name":"Spark","optional":false},{"name":"Synthetic Data","optional":false},{"name":"VLM","optional":false}],"status":"live","first_seen_at":"2026-01-09T23:26:33Z","employer_posted_date":"2026-01-09","last_verified_at":"2026-10-19T06:01:09Z","board_verified":true,"closed_at":null,"days_open":282,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":282},"description":"About the Company\nModels 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.\nAt 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) and pretraining with domain-specific data (The Finetuner’s Fallacy).\nWe 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.\nThis role is based in San Mateo, CA. We are in office 4 days a week.\nAbout the Role\nWe 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.\nThis 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.\nWhat You’ll Work On\nEmbed deeply with strategic customers to understand their data curation needs, business challenges, and technical requirements in detail.\nLead end-to-end customer PoCs that connect data curation, training behavior, evaluation outcomes, including dataset analysis, training plan design, and results interpretation.\n\nPartner with customer ML teams to map data & curation strategy\n\nDesign and execute evaluation plans for base and post-trained models, selecting appropriate benchmarks/metrics, and running model evaluations\n\nProduce customer-ready evaluation reports: methodology, metrics, baselines, ablations (e.g., curated vs raw), conclusions, and recommended next steps for productionization.\n\nCommunicate technical results to both ML experts and exec stakeholders, including tradeoffs in compute, latency, and deployment cost.\n\nCollaborate 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.\n\nProvide technical guidance, training, and clear documentation to ensure prospects can confidently assess the solution.\n\nAbout You\n4+ years of experience in software, ML platform, solutions, or customer engineering roles, with significant experience driving technical pre-sales engagements and PoCs.\n\nStrong 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.\n\nDemonstrated 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.\n\nExamples of the kinds of practical deep learning questions you might have to answer for customers:\nWhat’s the difference between MMLU, MMMU, and MMMLU?\n\nIs SWE-Bench a useful eval for base models?\n\nWhat’s a standard context window for pretraining, and what are the costs and benefits of changing it?\n\nWhat’s the difference between CPT and midtraining?\n\nCan we just compare your data to Qwen3?\n\nWill your data work with our model architecture?\n\nStrong programming skills in Python (or equivalent); able to prototype quickly and iterate with customers.\n\nExperience with data processing / distributed systems (e.g., Spark, Ray, data lakes/warehouses) and comfort working with large-scale datasets.\n\nFamiliarity with modern ML infrastructure: PyTorch/Hugging Face ecosystems, distributed training concepts, and deployment environments across cloud/on-prem/hybrid.\n\nFamiliarity with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).\n\nStrong communication skills, with the ability to translate complex ML and systems topics for diverse audiences.\n\nRequired to travel to customer sites as needed to support pre-sales engagements.\n\nCompensation\nAt 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.\nStarting pay is based on job-related skills, experience, qualifications, and interview performance.\n\nBenefits:\n100% covered health benefits (medical, vision, and dental).\n\n401(k) plan with a generous 4% company match.\n\nUnlimited PTO policy\n\nPaid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.\n\nAnnual $2,000 wellness stipend.\n\nAnnual $1,000 learning and development stipend.\n\nDaily lunches and snacks are provided in our office!\n\nRelocation assistance for employees moving to the Bay Area.","description_format":"text","description_chars":6199,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Parental leave","Relocation assistance","Unlimited PTO"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Artificial Intelligence","Machine Learning","AI Training Data & Annotation","AI Research Labs"],"lifecycle":[{"event":"open","at":"2026-09-06T12:36:30Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 5 · green card filings: 1","filings_12m":5,"filings_prev_12m":2,"green_card_filings_12m":1,"median_offered_wage_usd":229167,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":0}],"liveness":{"score":5,"band":"cold","label":"Long shot","p_open":1,"p_active":0.167,"p_room":0.28,"age_days":282,"expected_fill_days":48,"reasons":["conf:3","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-10-19T05:45:15Z"},"pay":{"stated_usd_annual":300000,"is_top_pay":true},"html_url":"https://alion.io/job/datologyai-solutions-engineer-aiml-pre-sales","json_url":"https://alion.io/job/datologyai-solutions-engineer-aiml-pre-sales.json","meta":{"generated_at":"2026-10-19T06:06:14Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":3776,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-20T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":9100},"rest":"https://alion.io/mcp/rest/get_company?id=9100"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fdatologyai-solutions-engineer-aiml-pre-sales"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fdatologyai-solutions-engineer-aiml-pre-sales"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fdatologyai-solutions-engineer-aiml-pre-sales"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/datologyai-solutions-engineer-aiml-pre-sales\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fdatologyai-solutions-engineer-aiml-pre-sales"}]}