Tampa, 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 Tampa.
What We Place
Representative roles
Platforms and technologies
Our Approach
This editorial hiring guide starts with sourced Tampa business context. Tampa's resilience strategy identifies life sciences and health care, financial and professional services, and logistics and distribution as growth clusters. These sectors create separate requirements for protected data, controlled transactions, and physical movement. 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 Tampa 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
List the production decisions the hire must own. Use those decisions to assess candidates whose prior title or industry differs from the opening. 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
1,730
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 1.196 jobs per one thousand across the metro workforce.
Employment concentration
0.71 location quotient
Tampa-St. Petersburg-Clearwater, FL reports a below-national employment concentration for this proxy occupation. Decide which requirements justify a wider regional or remote search.
Annual wage reference
$67,530 to $161,480
The metro median is 9% below the national Data Scientists median. Do not use the gap to discount niche platform or domain experience. BLS reports a $109,990 median for the proxy occupation in Tampa-St. Petersburg-Clearwater, 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 Tampa demand, clients, or candidate supply.
Sourced life sciences and health care context
The City of Tampa's Resilient Tampa strategy names life sciences and health care among the growth industries targeted through regional economic-development work. 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. Health-related systems can join patient or research data, service delivery, laboratories, billing, workforce, compliance, access reviews, and uptime requirements under several process owners.
Evidence to request: Ask for a pipeline diagram or repository structure that shows lineage, repeatable environments, and artifact retention. Set the care, research, product, or administrative boundary, record authority, protected data, integration path, access controls, validation need, downtime limit, and reviewer.
Sourced financial and professional services context
Resilient Tampa also identifies financial and professional services as a growth cluster for business attraction and workforce coordination. 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. Financial and client-service work may involve accounts, contracts, transactions, advice, approvals, regulated records, time entry, billing, reporting, and evidence for review.
Evidence to request: Review a release-control example with test gates, registry state, deployment strategy, and rollback steps. Name the service and customer, transaction or case lifecycle, system of record, control owner, approval chain, reporting deadline, data rights, and acceptance evidence.
Sourced logistics and distribution context
The Tampa strategy includes logistics and distribution among the clusters used to diversify the city's economic base. Set operating ownership for model services and training jobs. Include capacity, cost, feature freshness, prediction quality, and rollback signals in the interview scenario. Distribution systems must align orders, inventory, warehouses, ports, carriers, status events, exceptions, customer commitments, and billing while goods remain in motion.
Evidence to request: Use an incident involving stale features, failed training, or degraded predictions and score the candidate's diagnosis path. Map the order and shipment lifecycle, facilities, partner messages, volume peaks, event timing, exception queue, reconciliation, recovery target, and after-hours owner.
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 Tampa.
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 approved data use, evaluation records, human oversight, deployment boundaries, and security review. The public-sector and security work context is an editorial scenario, not a measured claim about Tampa.
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 Tampa.
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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