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Python Flask Jobs in Florida (NOW HIRING)

Citigroup, Inc.

Cloud Engineer - Vice President

Tampa, FL · On-site

$125.60K - $188.40K/yr

Proficiency in Microservices (Spring Boot, Python frameworks like Flask/Django), Event-Driven Services, and Cloud-Native Development, including REST and GraphQL. * Experience with Container ...

GRVTY

Data Scientist - Senior

Tampa, FL · On-site

Proficiency with at least one Python web framework (Flask, FastAPI, Django, or similar). * Experience developing interactive data visualizations using Plotly, Seaborn, Matplotlib, Bokeh, or ...

GRVTY

Data Scientist - Senior

Tampa, FL · On-site

Proficiency with at least one Python web framework (Flask, FastAPI, Django, or similar). * Experience developing interactive data visualizations using Plotly, Seaborn, Matplotlib, Bokeh, or ...

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How much do python flask jobs pay per hour?

As of May 30, 2026, the average hourly pay for python flask in Florida is $43.81, according to ZipRecruiter salary data. Most workers in this role earn between $36.11 and $49.76 per hour, depending on experience, location, and employer.

What is a Python Flask job?

A Python Flask job typically involves developing web applications using the Flask framework, a lightweight and flexible web framework for Python. Responsibilities may include building APIs, handling request-routing, integrating with databases, and deploying applications. Flask developers often work with front-end technologies and cloud platforms to create scalable and efficient web solutions.

What are the key skills and qualifications needed to thrive in the Python Flask position, and why are they important?

To thrive as a Python Flask developer, you need a strong command of Python programming, a thorough understanding of Flask web framework concepts, and experience with RESTful API design and implementation. Familiarity with tools such as Git, Docker, and relational databases, as well as certifications in web development or related fields, are often beneficial. Excellent problem-solving skills, effective communication, and the ability to work collaboratively in agile teams set standout candidates apart. These skills ensure high-quality, scalable application development and efficient teamwork in a dynamic tech environment.

What are some typical daily responsibilities for a Python Flask developer?

As a Python Flask developer, your daily tasks often include designing and building web application features, developing and maintaining RESTful APIs, and troubleshooting code issues. You'll frequently collaborate with front-end developers, QA engineers, and product managers to ensure seamless integration and alignment with project goals. Keeping codebases well-documented and participating in code reviews are also common aspects of the role. Additionally, you'll likely be involved in deploying applications to production environments and staying updated with industry best practices for security and performance.
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Python Flask jobs near you
AI Software Engineer

AI Software Engineer

Tampa Brass & Aluminum Corp

Tampa, FL

Full-time

Posted 17 days ago

Job description

ABOUT THE ROLE
We are looking for a deeply technical engineer who lives and breathes AI infrastructure - someone who can build, deploy, and scale production LLM systems from bare metal to browser. This is not a prompt-engineering role. We need someone who understands how transformers actually work, can diagnose bottlenecks at the infrastructure level, and builds reliable, observable systems around fundamentally probabilistic models.
You will own the full lifecycle of AI model deployment and play a key role in ensuring seamless CI/CD, infrastructure reliability, security, and performance across our environments.
WHAT YOU'LL DO
- Design and operate high-availability LLM inference clusters using vLLM, SGLang, and NVIDIA Triton
- Build AI-powered tools and customer-facing products with React frontends and Python/FastAPI backends
- Manage Kubernetes clusters (k8s, k3s, RKE2) end-to-end: provisioning, networking, GPU operator configuration, and upgrades
- Establish and maintain CI/CD pipelines for model packaging, container builds, and automated deployments
- Evaluate, fine-tune, and benchmark open-weight models for specific downstream tasks
- Build RAG pipelines and agentic workflows using vector databases and tool-calling frameworks
- Instrument infrastructure with monitoring and observability tooling to surface latency, throughput, and resource metrics
- Deploy and maintain AI systems in compliance-sensitive environments (CMMC, FedRAMP, ITAR)
- Maintain documentation of architectures, configurations, and processes across projects
- Track and manage tasks across concurrent projects using Kanban tools (ClickUp, Jira)
REQUIRED SKILLS
AI / ML & Inference
- SGLang, vLLM, Ollama, OpenWebUI
- NVIDIA Triton Inference Server, NVIDIA NIM, NVIDIA NeMo, TensorRT
- CUDA, cuBLAS, cuDNN, NCCL (multi-GPU)
- Hugging Face Transformers, LangChain, LlamaIndex
- Model quantization: GGUF, AWQ, GPTQ
- Fine-tuning: LoRA / QLoRA
- LLM architecture: transformers, attention mechanisms, KV cache
- RAG pipelines, embeddings, and vector search
- Agent frameworks: function calling, tool use
- RLHF, DPO, and SFT concepts
- Multimodal models (vision + text)
- Model benchmarking: MMLU, HumanEval, MT-Bench
- AI safety, output filtering, and prompt engineering
Linux & Systems
- Linux (Ubuntu / RHEL / SLES), Bash, systemd
- Networking fundamentals: iptables, VLAN, BGP
- SELinux / AppArmor
Languages & Frameworks
- Python, JavaScript / TypeScript, React
- FastAPI / Flask, Node.js
- REST, WebSocket, and SSE APIs
- SQL (PostgreSQL / SQLite), Redis
- Vector databases: Milvus, Qdrant, pgvector
DevOps / CI/CD & Infrastructure
- Kubernetes (k8s), k3s, RKE2, Helm, Kustomize
- Rancher, ArgoCD, Flux CD
- Docker / Podman, container registries
- Ingress-NGINX / Traefik, cert-manager, MetalLB
- GitHub Actions, GitLab CI, Jenkins
- Terraform, Pulumi, Ansible
- Prometheus, Grafana, OpenTelemetry, ELK Stack
- Vault (secrets management)
NICE TO HAVE
- Multi-node tensor parallelism and pipeline parallelism
- Experience deploying AI in air-gapped or classified environments
- Open-source contributions to AI or inference tooling
- Distributed systems background (Raft, consensus, replication)
- Rust or Go for high-performance tooling
- Active DoD security clearance

Apply