St. Louis, MO
MLOps engineers who bridge data science and production. Crosscheck recruits AI/ML & LLM Engineering candidates for contract, contract-to-hire, and permanent roles tied to St. Louis.
What We Place
Representative roles
Platforms and technologies
Our Approach
This editorial hiring guide starts with sourced St. Louis business context. St. Louis Development Corporation identifies geospatial technology, health care innovation, advanced manufacturing, and agricultural technology as drivers of the city economy. Those sectors give hiring teams separate data, security, production, and supply-chain settings for technical searches. An MLOps Engineer owns the controls that move models from experiments into supported services. The search brief should name the training environment, registry, deployment targets, approval path, observability stack, and teams that share the platform.
Source MLOps engineers with production ownership of model pipelines and serving infrastructure
Vet on model serving, experiment tracking, feature stores, and retraining workflows
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
Separate platform construction from day-to-day model operations. Some teams need reusable pipelines and infrastructure; others need release governance, incident response, cost control, or migration from manually operated notebooks. The three sourced St. Louis 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
An industrial brief should show how software, data, and infrastructure connect to plants, equipment, schedules, quality, and frontline users. 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 MLOps 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
2,640
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 1.969 jobs per one thousand across the metro workforce.
Employment concentration
1.17 location quotient
St. Louis, MO-IL 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
$59,500 to $158,310
The metro median is 17% below the national Data Scientists median. Do not use the gap to discount niche platform or domain experience. BLS reports a $99,600 median for the proxy occupation in St. Louis, MO-IL.
Hiring brief scenarios
These scenarios connect location context to role responsibilities. Use them as prompts to verify with the employer, not as measures of St. Louis demand, clients, or candidate supply.
Sourced geospatial technology context
A current St. Louis Development Corporation feature names geospatial technology as a driver of the city economy and describes T-REX as an innovation center that works with the National Geospatial-Intelligence Agency. Require reproducible training and lineage for the local data setting. The candidate should account for code, configuration, data versions, model artifacts, and approval records without copying sensitive data into uncontrolled tools. Geospatial systems can join imagery, sensor feeds, location records, analytical models, map services, access controls, and delivery partners across restricted and public data sets.
Evidence to request: Ask for a pipeline diagram or repository structure that shows lineage, repeatable environments, and artifact retention. Define the geographic product, source data, coordinate and accuracy rules, security boundary, model or service interface, update cycle, and approving user.
Sourced health care innovation context
The same St. Louis Development Corporation source identifies health care innovation among the industries that drive the city economy. Define promotion between development, test, and production. Ask who approves a model, which automated checks block release, and how the team handles a failed deployment. Health innovation work may cross research data, patient or member records, laboratories, devices, billing, workforce systems, access review, and formal release controls.
Evidence to request: Review a release-control example with test gates, registry state, deployment strategy, and rollback steps. Name the care, research, product, or business process, record authority, protected data, integration path, validation evidence, downtime limit, and reviewer.
Sourced advanced manufacturing and agricultural technology context
St. Louis Development Corporation also names advanced manufacturing and agricultural technology among the industries that shape the city economy. Set operating ownership for model services and training jobs. Include capacity, cost, feature freshness, prediction quality, and rollback signals in the interview scenario. These operations can connect product formulas or designs, equipment, plants, growers or suppliers, quality, inventory, warehouses, maintenance, traceability, and financial postings.
Evidence to request: Use an incident involving stale features, failed training, or degraded predictions and score the candidate's diagnosis path. Trace one product from design or source through production, quality release, storage, shipment, accounting, exception handling, and change ownership.
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. MLOps Engineer: Kubeflow
Choose a Kubeflow decision from your work as MLOps Engineer. Which constraint changed the design, and what evidence supported the result?
Use the answer to assess sensor or production data, edge constraints, model drift, operator review, and measurable process outcomes. The manufacturing and operational systems context is an editorial scenario, not a measured claim about St. Louis.
2. ML Platform Engineer: MLflow
Describe project work you completed as ML Platform Engineer involving MLflow that did not follow the original plan. What did you own, and how did you correct it?
Use the answer to assess sensor or production data, edge constraints, model drift, operator review, and measurable process outcomes. The manufacturing and operational systems context is an editorial scenario, not a measured claim about St. Louis.
3. AI Infrastructure Engineer: Metaflow
For a Metaflow 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 sensor or production data, edge constraints, model drift, operator review, and measurable process outcomes. The manufacturing and operational systems context is an editorial scenario, not a measured claim about St. Louis.
Need the full MLOps 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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