Minneapolis, MN
LLM engineering recruiting for production systems. Crosscheck recruits AI/ML & LLM Engineering candidates for contract, contract-to-hire, and permanent roles tied to Minneapolis.
What We Place
Representative roles
Platforms and technologies
Our Approach
This editorial hiring guide starts with sourced Minneapolis business context. Minneapolis's 2025 to 2029 consolidated plan provides a citywide sector table for education and health care, finance and real estate, information, manufacturing, professional services, public administration, and transportation. The dated table supports distinct service, control, and operating scenarios without attributing demand to a specific employer. An LLM Engineer brief should name the model boundary, retrieval sources, evaluation method, and production owner. API use alone does not show that a candidate can design grounded responses, control model behavior, or support an AI feature after launch.
Source LLM engineers who have shipped production retrieval, fine-tuning, inference, or evaluation systems
Assess candidates through architecture decisions, model tradeoffs, and evaluation methods
target a first candidate slate within 48 hours for qualified exclusive searches in our core disciplines after a completed intake
Permanent placements include a 90-day replacement guarantee, subject to the signed agreement.
Start the search
Include the business context, systems, delivery phase, work model, compensation, and interview timeline. A Crosscheck search lead will use that context to calibrate the role before sourcing begins.
Local Market Brief
Decide whether the hire owns retrieval, model adaptation, application code, evaluation, or the full service. Record latency, cost, privacy, and failure-response requirements before sourcing so recruiter review can distinguish prompt experimentation from production engineering. The three sourced Minneapolis contexts below turn that scope into intake and screening decisions. They do not measure current vacancies, candidate supply, or Crosscheck client activity.
Editorial market scenario
Give candidates the integration, approval, audit, and change-management boundaries during the interview. Ask for comparable decisions from prior work. This is planning guidance, not measured local demand.
Editorial industry scenario
A health-sector brief should name the protected data, validation, availability, and user-workflow requirements the person will handle. Confirm that this context applies to the employer before using it in the search.
Screening focus
We test for model or application ownership, evaluation discipline, data judgment, and evidence that the candidate has shipped reliable AI systems.
Published labor benchmark
BLS does not publish an occupation matching LLM Engineer. Crosscheck uses Data Scientists (15-2051) as the closest published broad benchmark; it is not a count or pay estimate for this exact specialty.
BLS OEWS May 2025, published May 15, 2026
Published metro employment
3,250
BLS publishes a narrower metro employment estimate for the proxy occupation. Screen for adjacent experience that transfers without lowering the production bar. The estimate equals 1.664 jobs per one thousand across the metro workforce.
Employment concentration
0.99 location quotient
Minneapolis-St. Paul-Bloomington, MN-WI sits near the national employment concentration for this proxy occupation. Use role evidence and work-model requirements to set the sourcing radius.
Annual wage reference
$71,990 to $195,530
The metro median is 8% above the national Data Scientists median. Test whether the role's scope and location requirement support that difference. BLS reports a $129,780 median for the proxy occupation in Minneapolis-St. Paul-Bloomington, MN-WI.
Hiring brief scenarios
These scenarios connect location context to role responsibilities. Use them as prompts to verify with the employer, not as measures of Minneapolis demand, clients, or candidate supply.
Sourced education and health care services context
The City of Minneapolis sector table reports education and health care services as its largest listed job category. The plan uses the table as part of the city's economic development market analysis. Connect the local operating context to the data that may enter prompts or retrieval. Require a candidate to explain document preparation, permissions, citation behavior, evaluation cases, and the team that approves changes. Education and health environments can combine student, patient, workforce, research, grant, scheduling, finance, and identity records with different privacy and retention rules.
Evidence to request: Request an evaluation set, retrieval diagram, or redacted design note that shows how the candidate tested grounding and access boundaries. Choose the actual institutional process, name the protected records and user groups, and set the integration, access review, audit, calendar, and operational acceptance requirements.
Sourced finance, insurance, and real estate context
Minneapolis's economic development market analysis lists finance, insurance, and real estate as a separate business sector with both worker and job counts. Set the model-selection decision around the workload rather than a preferred vendor. Ask how the engineer compared hosted and open models, measured quality, handled unsafe output, and controlled latency or token cost. Finance and property processes may join customers, accounts, policies, leases, assets, payments, valuations, approvals, and regulatory evidence across systems with fixed close dates.
Evidence to request: Use a design exercise with a fixed quality target and cost limit. Score the tradeoffs, measurement plan, and fallback behavior. Define the transaction or property lifecycle, calculation authority, posting system, approval matrix, data retention, reconciliation, exception queue, and period-end deadline.
Sourced professional, scientific, and management services context
The Minneapolis plan also separates professional, scientific, and management services from information and manufacturing in its city sector table. Treat launch support as part of the role. The brief should cover observability, feedback review, version changes, rollback, and ownership when retrieval or model behavior produces a poor result. Professional and scientific work can cross client agreements, project records, analytical methods, intellectual property, staff allocation, billing, and internal platforms with changing delivery teams.
Evidence to request: Ask for an incident or regression account with the signal, diagnosis, change, and post-release check the candidate owned. State whether the role owns a client deliverable, analytical method, internal service, or business platform, then define information boundaries, acceptance evidence, billing dependency, and handoff rules.
Interview scorecard
Ask each candidate the same core questions. Score the evidence, ownership, and judgment in the answer instead of relying on job-title or keyword matches.
1. LLM Engineer: OpenAI GPT-4o / o1
Choose an OpenAI GPT-4o / o1 decision from your work as LLM Engineer. Which constraint changed the design, and what evidence supported the result?
Use the answer to assess data provenance, evaluation by use case, human review, privacy, and production monitoring. The healthcare and life-science systems context is an editorial scenario, not a measured claim about Minneapolis.
2. Prompt Engineer: Anthropic Claude
Describe project work you completed as Prompt Engineer involving Anthropic Claude that did not follow the original plan. What did you own, and how did you correct it?
Use the answer to assess data provenance, evaluation by use case, human review, privacy, and production monitoring. The healthcare and life-science systems context is an editorial scenario, not a measured claim about Minneapolis.
3. RAG Architect: Llama 3 / Mistral / Gemma
For a Llama 3 / Mistral / Gemma system you supported, explain the handoff, operating limits, and measures used after launch. Where did your responsibility begin and end?
Use the answer to assess data provenance, evaluation by use case, human review, privacy, and production monitoring. The healthcare and life-science systems context is an editorial scenario, not a measured claim about Minneapolis.
Need the full LLM Engineer evaluation guide?
The role guide covers technical scope, interview questions, and evidence checks once, without repeating the same material on every city page.
FAQ
For qualified exclusive searches in our core disciplines, Crosscheck targets a first candidate slate within 48 hours after a completed intake. Contract placements include a 40-billable-hour replacement guarantee, and permanent placements include a 90-day replacement guarantee, subject to the signed agreement.
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