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Assistant Mlops Jobs in Florida (NOW HIRING)

Apex Systems

AI engineer

Fort Lauderdale, FL · On-site

$109K - $131K/yr

You will operate within the architecture and MLOps standards set by the team while having the ... Develop NLP and speech models for call summarization, sentiment analysis, and agent assist tools.

Socket.dev

Principal AI Engineer - Vice President

Tampa, FL · On-site

$120 - $160/hr

... OpenAI Assistants, CrewAI, AutoGen, custom orchestrators). * Define the end‑to‑end AI system ... Build and support production‑grade MLOps / AIOps pipelines, including CI/CD, automated testing ...

Total Quality Logistics

AI Architect

Tampa, FL · On-site

MLOps, Governance & Operational Readiness * Define and implement enterprise MLOps standards for ... teams that assist with accounting, and after hours calls and specific needs. At TQL, the ...

TQL

AI Architect

Tampa, FL · On-site

$59.50 - $78.50/hr

... assistants* Application Architecture & Integration* Design how AI services integrate with core ... MLOps, Governance & Operational Readiness* Define and implement enterprise MLOps standards for ...

Vultus Inc

AI/ML Engineer

Miami, FL · On-site +1

$120K - $150K/yr

Familiarity with MLOps tools and model monitoring. * Experience building AI-powered chatbots or intelligent assistants. * Relevant certifications in AI, Machine Learning, or Cloud technologies.

540

Security Operations Engineer

Satellite Beach, FL · On-site

Support vulnerability management, scanning, and remediation efforts * Assist in monitoring system ... Experience securing machine learning operations (MLOps) * Familiarity with cloud security concepts

Armaninollp

Data & AI Platform Engineer

Boca Raton, FL

$108K - $130K/yr

Data/Analytics Tooling Support * Assist teams with onboarding and "how-to" enablement across a core ... MLOps). "Armanino" is the brand name under which Armanino LLP and Armanino Advisory LLC ...

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Assistant Mlops information

What is an Assistant MLOps?

Assistant MLOps are professionals who support the deployment, monitoring, and management of machine learning models in production environments. They assist senior MLOps engineers with tasks like automating workflows, managing data pipelines, maintaining infrastructure, and ensuring model performance. Their role bridges the gap between data science and IT operations, helping organizations scale and maintain their AI solutions efficiently. Assistant MLOps often have knowledge of cloud services, CI/CD tools, and basic programming, and they work closely with data scientists and engineers.

What are the typical daily responsibilities of an Assistant MLOps?

As an Assistant MLOps professional, you can expect your daily tasks to involve supporting the deployment, monitoring, and maintenance of machine learning models in production environments. This often includes collaborating with data scientists to automate model training and testing workflows, managing cloud-based resources, and ensuring that data pipelines are running smoothly. You'll also help troubleshoot issues related to model performance or infrastructure and assist in implementing best practices for version control and continuous integration. Working closely with both engineering and data teams, you'll play a key role in ensuring that ML models remain reliable and scalable in real-world applications.

What are the key skills and qualifications needed to thrive as an Assistant MLOps?

To thrive as an Assistant MLOps, you need a solid understanding of machine learning fundamentals, programming (especially Python), and experience with cloud platforms; a degree in computer science or a related field is typically preferred. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and version control systems (e.g., Git) is important, and certifications in cloud services (AWS, Azure, GCP) can be advantageous. Strong problem-solving, communication, and collaboration skills help you bridge the gap between data science and operations teams. These combined skills ensure efficient deployment, monitoring, and maintenance of machine learning models in production environments.

What is the difference between Assistant Mlops vs Data Engineer?

AspectAssistant MlopsData Engineer
Required CredentialsCertifications in cloud platforms, basic scripting, ML toolsComputer science degree, SQL, Python, data architecture
Work EnvironmentCollaborates with ML teams, supports deployment pipelinesBuilds data pipelines, manages databases, processes large datasets
Industry UsageAI/ML projects, cloud-based environmentsData infrastructure, analytics, big data solutions

Assistant Mlops and Data Engineer roles share overlapping skills in cloud platforms and scripting. However, Assistant Mlops focuses on supporting ML deployment and operations, while Data Engineers primarily build and maintain data infrastructure. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are the most commonly searched types of Mlops jobs in Florida?

The most popular types of Mlops jobs in Florida are:

What are popular job titles related to Assistant Mlops jobs in Florida?

For Assistant Mlops jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Assistant Mlops jobs in Florida look for?

The top searched job categories for Assistant Mlops jobs in Florida are:

What cities in Florida are hiring for Assistant Mlops jobs?

Cities in Florida with the most Assistant Mlops job openings:

Assistant Mlops jobs near you

MLOPs Engineer

Compusoft Integrated Solutions, Inc.

Miami, FL • On-site

Other

Posted 5 days ago

Job description

Title: MLOPs Engineer

Location: Hybrid Role (South Florida Preferred)

Duration: 6+ Months (Must be able to convert FTE WITHOUT SPONSORSHIP)

Required Skills:

  • 8+ years of Machine Learning Engineering or applied AI experience.
  • 3+ years in Lead, Principal, or senior technical leadership roles.
  • Strong hands-on Python development for production-grade machine learning solutions.
  • Advanced experience with Databricks, MLflow, and distributed machine learning workloads.
  • Expertise with TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.
  • Proven experience building and deploying large-scale recommendation engines.
  • Strong experience developing customer personalization and customer intelligence solutions.
  • Experience with customer segmentation, churn prediction, and customer value models.
  • Strong understanding of Customer 360 platforms and unified customer data.
  • Experience using identity graphs to improve customer matching and prediction accuracy.
  • Strong feature engineering, model evaluation, validation, and lifecycle management experience.
  • Experience designing scalable batch and real-time inference architectures.
  • Proven experience deploying, monitoring, and retraining machine learning models in production.
  • Experience partnering with Data Engineering teams to create ML-ready datasets.
  • Strong architecture experience across Data Science, Engineering, and MLOps platforms.
  • Experience leading technical design reviews and establishing enterprise ML standards.
  • Strong mentoring, stakeholder communication, and cross-functional technical leadership skills.

Preferred Skills:

  • Experience with Snowflake and integrated Databricks data environments.
  • Experience building GenAI, LLM-powered, or agentic AI applications.
  • Experience developing domain-specific AI agents and intelligent assistants.
  • Knowledge of MLOps, feature stores, model serving, and automated retraining.

Experience with real-time recommendation and streaming personalization platforms

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