Jacksonville, FL
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 Jacksonville.
What We Place
Representative roles
Platforms and technologies
Our Approach
This editorial hiring guide starts with sourced Jacksonville business context. Jacksonville's Office of Economic Development separates advanced manufacturing, aviation and aerospace, finance and insurance, information technology, life sciences, and logistics and distribution. Those sectors create distinct requirements for transactions, protected records, products, and freight. 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 Jacksonville 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
Tie each must-have requirement to a task, system, risk, or deadline. Remove industry preferences that do not change how the person will perform the job. This is planning guidance, not measured local demand.
Editorial industry scenario
A finance-facing brief should identify the transaction, reporting, audit, privacy, and availability requirements attached to the role. 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
880
BLS publishes fewer than one thousand metro jobs for the proxy occupation. Treat the estimate as a reason to define location flexibility before outreach. The estimate equals 1.146 jobs per one thousand across the metro workforce.
Employment concentration
0.68 location quotient
Jacksonville, FL reports a below-national employment concentration for this proxy occupation. Decide which requirements justify a wider regional or remote search.
Annual wage reference
$62,710 to $165,370
The metro median sits within five percent of the national Data Scientists median. Validate the budget against seniority, scope, and current salary data. BLS reports a $122,680 median for the proxy occupation in Jacksonville, FL.
Hiring brief scenarios
These scenarios connect location context to role responsibilities. Use them as prompts to verify with the employer, not as measures of Jacksonville demand, clients, or candidate supply.
Sourced finance, insurance, and information technology context
Jacksonville's Office of Economic Development lists finance and insurance and information technology among its targeted industries and connects the technology cluster with the city's financial-services base. 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. These systems can join customer accounts, policies, payments, claims, identity, fraud controls, digital services, approvals, reconciliations, reporting, and release support.
Evidence to request: Ask for a pipeline diagram or repository structure that shows lineage, repeatable environments, and artifact retention. Name the product and transaction, system of record, money or claim flow, identity model, control owner, reporting deadline, reconciliation, release path, and support target.
Sourced life sciences context
The Jacksonville economic-development page names life sciences as a targeted industry and describes medical research facilities, health systems, and medical products and services. 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. Life-sciences work may cross research data, patient records, laboratories, medical products, protected information, validation, manufacturing, billing, and enterprise systems.
Evidence to request: Review a release-control example with test gates, registry state, deployment strategy, and rollback steps. Set the research, product, care, or administrative boundary, source record, validation protocol, device or lab interface, access controls, release authority, and reviewer.
Sourced manufacturing, aerospace, and logistics context
Jacksonville also targets advanced manufacturing, aviation and aerospace, and logistics and distribution and describes city port, airport, rail, interstate, and industrial-site infrastructure. 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 engineering definitions, plants, aircraft or components, quality, maintenance, inventory, ports, warehouses, carriers, status events, and financial settlement.
Evidence to request: Use an incident involving stale features, failed training, or degraded predictions and score the candidate's diagnosis path. Trace the product, aircraft component, or shipment through source, production or maintenance, quality release, inventory, transport, customer handoff, exception, and accounting.
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 model evaluation, sensitive-data handling, explainability, and controls around automated decisions. The finance and insurance systems context is an editorial scenario, not a measured claim about Jacksonville.
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 forecast or routing evaluation, changing inputs, latency, exception handling, and business review. The logistics and distribution operations context is an editorial scenario, not a measured claim about Jacksonville.
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 model evaluation, sensitive-data handling, explainability, and controls around automated decisions. The finance and insurance systems context is an editorial scenario, not a measured claim about Jacksonville.
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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