Top Python Jobs in Miami, FL

Develop and ship backend and frontend features that improve school-family communication. Collaborate with product and design, champion AI/LLM-driven workflows, build scalable secure services on AWS, evolve monolithic systems, participate in code reviews, and help shape architecture.

Design, build, and operate scalable AWS-based platform infrastructure for data processing. Improve pipeline automation, monitoring, security, and reliability. Lead CI/CD, IaC (Terraform/Scalr), network design, and incident response; collaborate with cross-functional teams and participate in on-call rotation. Integrate AI tools to streamline development and troubleshooting.

Lead a developer pod to design and deliver UiPath-based Agentic/RPA solutions. Provide technical design, mentor engineers, configure UiPath AI Trust Layer and LLM interfaces, integrate systems via APIs, and drive customer adoption and evangelism of the UiPath platform.

Define and drive full-stack architecture and technical vision across teams, write high-quality production code, lead zero-to-one projects, productionize ML systems, own reliability and SLOs, mentor senior engineers, and align engineering roadmaps with product and company strategy.

Design, develop, and document Salesforce solutions (Apex, LWC, Visualforce) and integrations; lead small developer teams; build APIs, data migrations, and test plans; ensure code quality and mentor others while evaluating and adopting AI-enabled tools.

The Senior DevOps Engineer will build secure, scalable infrastructure on AWS, manage Kubernetes platforms, and oversee FedRAMP-related tasks while ensuring compliance and operational efficiency.

Manage a team of cloud engineers to govern and optimize a multi-cloud environment while implementing security frameworks and managing vendor relationships.

The Site Reliability Engineer will lead technical initiatives, architect solutions, troubleshoot issues, mentor team members, and improve observability practices.

The Cloud Administrator manages cloud infrastructure and services, ensuring their performance, security, and reliability while troubleshooting issues and optimizing costs.

Lead technical design and architecture of large-scale Ceph clusters, drive capacity planning and major upgrades, resolve complex cross-functional production incidents, establish automation and reliability standards, and mentor engineers on advanced Ceph operations to scale the global storage platform.

Lead enterprise data architecture and platform engineering efforts using Databricks Lakehouse. Design scalable cloud-native data platforms, implement medallion architectures, enable data governance and AI/ML workloads, build automation and CI/CD for Databricks, and mentor teams while collaborating with stakeholders on strategy and delivery.

Build and maintain full-stack product features, backend services, APIs, data pipelines, and AI integrations to transform customer interaction data into AI-powered experiences. Collaborate with cross-functional teams to design, test, and support production systems, internal tools, and user-facing interfaces. Own ambiguous problems end-to-end and raise engineering quality across the data and AI platform.

Design, build, and operate reliable backend systems while mentoring engineers, participating in design discussions, and improving system performance.

Embedded with strategic customers, own end-to-end design, build, and production rollout of cloud infrastructure for large-scale GPU/HPC AI workloads. Build compute orchestration, platform services, onboarding sandboxes, and reliability/security tooling. Turn field learnings into reusable platform capabilities and partner with Product and Engineering to productize them.

The Lead Systems HPC Engineer will optimize GPU clusters' performance, troubleshoot issues, integrate new hardware, and collaborate with teams on system-level software development.

Design and build systems for managing bare-metal infrastructure, focusing on automation, hardware provisioning, and software integration with Linux systems.

Designs and implements middleware, APIs, and data exchange to integrate Appian, Palantir, and VA financial systems. Builds secure, auditable integrations, supports ATO/FedRAMP activities, develops tests and runbooks, troubleshoots production issues, and mentors junior engineers.

As a Machine Learning Engineer in Computer Vision, you'll develop AI solutions using advanced algorithms, focusing on image classification, segmentation, and video processing tools.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

Embed with strategic clients to design, build, and ship production Python code and data pipelines. Integrate RESTful APIs, optimize complex SQL, architect scalable data workflows, lead technical discovery and workshops, and translate operational needs into product improvements while ensuring mission-critical outcomes.

Design, build, and scale low-latency distributed platform components; define technical vision and architecture; collaborate with product and ML teams; evaluate build-vs-buy decisions; prototype research breakthroughs and deliver robust, production-grade services.

Build and own production backend services in Python for a large-scale ecommerce search platform. Work with SQL-heavy systems, monitoring/alerting, and debugging user-facing systems. Deliver maintainable software via tests, code review, and incremental delivery. Collaborate on data integrations and optional ETL/ELT workflows with PySpark; apply SEO, API/auth, and unstructured data knowledge when needed.

Build and maintain Python backend services for experiment assignment, logging, and report generation. Improve scalability, performance, and reliability of experiment reporting pipelines. Add product-facing UI features, take technical ownership of projects, and participate in weekly on-call rotation. Collaborate with Search/Recommendations, ML/DS, and customer-facing teams.

Lead design and development of multi-tenant backend services and APIs for a space communications platform on AWS. Build scalable, secure services with automation, testing, and mentorship of junior engineers; interact with customers and partners and support operations for US government satellites.

Build and lead development of core backend platform services for a space communications ground system. Design and implement multi-tenant cloud-native APIs and services with automation and security, own features end-to-end, mentor junior engineers, and collaborate across teams to support US government satellite operations.