Top Remote Python Jobs in Miami, FL

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.

Own and maintain reliability, performance, scalability, and capacity of massive Ceph storage clusters. Troubleshoot distributed storage issues, build automation (Python/Shell, SaltStack, Ansible), define observability (SLIs/SLOs, PromQL/LogQL, Grafana), and lead lifecycle initiatives like upgrades, expansions, and migrations.

Provide system administration and operational support for lottery platforms: implement new customers, troubleshoot availability/performance, monitor capacity and security, manage incidents and SLAs, maintain monitoring/KB articles, and participate in a 24x7 on-call rotation. Work on product releases, enhancements, and upgrades across Linux, databases, containers, and cloud environments.

Build and evolve Nexus interfaces for Temporal SDKs across multiple languages. Design and implement runtime APIs and behaviors, integrate SDKs tightly with language runtimes for durable, deterministic execution, collaborate with OSS community, write technical documentation, and own end-to-end features with high reliability.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

Senior technical authority for IBM AIX and Power Systems architecture, engineering, migration, performance tuning, automation, and resiliency. Lead large-scale OS and hardware migrations, own lifecycle management, incident escalation/RCA, HA/DR design, and mentor L3 engineers while ensuring governance, compliance, and vendor coordination.

Develop and maintain backend solutions, ensuring performance, security, and regulatory compliance, while collaborating in cross-functional teams.

Lead and deliver complex customer implementations, debug and build integrations, drive architectural decisions, run technical discovery, mentor junior engineers, and write production/integration code (Python, JavaScript, SQL). Serve as technical escalation and represent FDE in product and cross-functional discussions.

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.

Partner with customers to deploy collaborative robots: perform onsite hardware/software testing, troubleshoot and repair, conduct readiness assessments, document procedures, replace parts/retrofits, and drive project communication to ensure successful long-term adoption.

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.

Build and maintain large-scale batch and streaming data ingestion and ETL pipelines for global geospatial datasets. Implement, test, monitor, and optimize backend services on AWS; integrate data with APIs; mentor engineers; reduce technical debt; and participate in design, code reviews, and on-call support to ensure data quality and operational excellence.

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.

Operate and troubleshoot Azure data platform environments (SQL Managed Instance, ADF, SSIS, Storage, App Services). Monitor and resolve incidents, validate backups, build automation and self-healing pipelines, maintain CI/CD in Azure DevOps, perform off-hours on-call duties, and continuously eliminate manual operational toil through scripting and Azure-native automation.

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.

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.