Top Remote Python Jobs in Miami, FL

Lead customer-facing HPC deployments and serve as the escalation point for complex hardware, operating system, application, and compiler issues. Deploy and debug GPU-accelerated Kubernetes clusters across on-premises and cloud environments, using Python, C#/.NET, CUDA, and ROCm. Diagnose issues involving NVIDIA and AMD GPUs, high-speed interconnects, PCIe topology, and driver stacks. Create technical documentation, reproduce customer failures, and collaborate with engineering and R&D on bug reports and product improvements.

Build and maintain scalable, internationalized React interfaces for a SaaS platform. Implement localization in front-end components, manage localization files, coordinate translation workflows, and validate localized builds across languages and regions. Partner with engineering, design, vendors, and localization teams to resolve UI and internationalization issues, support localization QA, and ensure release readiness. The role requires strong front-end development, localization engineering, testing, communication, and independent project management skills.

Join a remote engineering team to write, test, and maintain code under senior guidance; participate in code reviews, standups, and sprint planning; debug and resolve application issues; and continuously learn new technologies and best practices.

The Senior Formal Verification Engineer will verify ASICs using formal verification methods, ensuring correctness and collaborating with architects and designers across projects.

Lead the Performance and Quality Frameworks team, owning scalable performance engineering platforms and shared functional testing frameworks. Drive architecture, reliability, adoption, documentation, self-service, and roadmap execution across product teams. Apply AI tools such as Cursor and Claude Code to improve test development, maintenance, analysis, and engineering efficiency. Partner with cross-functional stakeholders, mentor engineers, measure framework outcomes, and support highly distributed SaaS systems using cloud, microservices, containers, and CI/CD technologies.

Build and improve Azure Kubernetes Service capabilities for Linux and Windows containers. Develop distributed cloud infrastructure, automation, observability tooling, and reliability improvements at global scale. Support AI-native infrastructure, including GPU orchestration, model deployment, inference, and platform operations. Accelerate engineering workflows, prevent production incidents, integrate AI tools, and contribute to Kubernetes and cloud-native platform innovation.

Develop firmware, backend systems, and tooling for cellular IoT devices. Responsibilities include C development for STM32 microcontrollers, embedded AI integration, cellular communication, low-power optimization, device debugging and validation, and backend development with Python and Ruby on Rails. The role collaborates with hardware, electronics, and manufacturing teams and requires independently leading complex development initiatives.

Designs, operates, and improves production database systems across MySQL, PostgreSQL, BigQuery, and Google Cloud Platform. Responsibilities include performance tuning, backup and recovery, replication, upgrades, schema changes, capacity planning, data integrity, disaster recovery, and database security. The role partners with engineering and data teams, automates operational work using scripting, infrastructure as code, and CI/CD, and participates in a scheduled 24x7 on-call rotation.

Build polished, responsive front-end applications for Chiri Brain and client-specific AI solutions. Design user flows, prototypes, interfaces, reusable components, and design systems while integrating APIs, authentication, business data, agent workflows, and security controls. Work directly with customers and stakeholders to understand needs, rapidly prototype, gather feedback, and ship production-quality software. Help establish scalable front-end architecture and use AI-assisted development tools to accelerate delivery.

Design, build, and optimize production-grade applications on Azure while contributing to an observability-focused Azure service. Responsibilities include developing cloud-native systems, creating reusable engineering assets, supporting production environments through on-call participation, investigating incidents, improving reliability and performance, and influencing Azure platform engineering through customer insights. The role also involves direct engagement with strategic customers and strengthening technical capabilities across the organization.

Lead development of AI infrastructure for large-scale GPU training and inference. Design workload scheduling, serving, orchestration, resource governance, failover, and multitenant Kubernetes platforms. Build reliable C# and Go services, optimize GPU fleet performance, and drive observability, diagnostics, and production operations. Provide technical leadership, architectural direction, mentoring, and cross-team collaboration across cloud infrastructure, hardware, networking, and AI deployment teams.

Build and lead data catalog infrastructure supporting data discovery, metadata management, governance, quality, lineage, privacy, access control, and retention. Develop scalable metadata integrations, onboarding tools, data policies, and end-to-end lineage products across online, offline, machine learning, metrics, visualization, and third-party datasets. Collaborate with cross-functional infrastructure teams to ensure Airbnb data assets are cataloged, discoverable, governed, and compliant with regulatory requirements.

Develop and maintain a TypeScript and Node.js application in a federal AWS environment. Responsibilities include troubleshooting defects across frontend, APIs, databases, integrations, containers, and cloud services; performing root-cause analysis; deploying secure fixes; supporting releases and incidents; and collaborating with Test Engineers. The role also tunes and evaluates AI models, prompts, workflows, retrieval settings, and integrations while maintaining security, traceability, governance, and change control.

The Lead Technology Engineer will lead IT systems implementation, ensure network security, manage integrations, and enhance operational efficiency through automation.

Build and maintain CI/CD pipelines, deployment automation, and cloud infrastructure across Azure and AWS. Manage observability with Datadog or Dynatrace, improve incident response and MTTR, provision infrastructure with Terraform, and develop automation scripts using Python, Bash, or PowerShell. Collaborate across VA engineering programs, improve platform stability, mentor junior engineers, and establish DevOps standards in a remote Agile environment.

Design and implement FPGA code for satellite digital payloads, including DSP algorithms, software-defined radio modulation and demodulation, and embedded processor interfaces. Develop custom IP, improve DSP and interface reliability, integrate vendor IP, and support communications architecture and spacecraft design studies. Participate across simulation, synthesis, place and route, timing closure, and hardware testing using Xilinx FPGAs and industry-standard HDL and simulation tools.

Leads the engineering organization for Polaris, overseeing strategy, architecture, people, delivery, quality, reliability, security, budgets, and vendor relationships. The VP scales engineering leadership, develops platform capabilities, advances AI-assisted development, manages cloud and data infrastructure, partners on product strategy, and ensures resilient, secure, observable systems. The role requires executive judgment, deep SaaS and cloud architecture expertise, and the ability to support critical incidents and complex technical decisions.

Own the reliability, availability, performance, observability, and security of Ophelia’s GCP telehealth platform. Define SLOs, improve monitoring and incident response, expand Terraform infrastructure, strengthen CI/CD, manage disaster recovery, and address latency and Cloud Run performance. Lead on-call maturity, HIPAA/SOC 2 infrastructure controls, and reliability education for engineers. Use AI-assisted tools for automation and incident triage while partnering with technical and non-technical stakeholders.

Provide L2/L3 production support for enterprise B2B integration and managed file transfer platforms. Administer, configure, deploy, monitor, patch, and troubleshoot Axway and related infrastructure, supporting partner onboarding, certificates, connectivity, incidents, changes, releases, disaster recovery, and high availability. Lead major incident restoration, root cause analysis, compliance activities, automation, and continuous improvement while coordinating customers, vendors, and global teams. Participate in a mandatory 24x7 on-call rotation and mentor junior engineers.

Leads software engineering for vector search and information retrieval capabilities in Azure data products. Designs complex architectures, develops high-quality and performant code, creates comprehensive test strategies, collaborates across research and engineering teams, and mentors engineers. Drives product integration, scalability, performance, release planning, and roadmap execution while applying expertise in algorithms, database internals, performance engineering, and AI-based retrieval.

Designs, deploys, integrates, validates, and operates infrastructure supporting large-scale AI compute clusters. Responsibilities include Linux systems, virtualization, storage, identity and security services, infrastructure automation, provisioning, testing, production acceptance, Tier 3 escalation, troubleshooting, reliability optimization, and lifecycle management. The role collaborates with engineering teams, vendors, NOC personnel, SREs, and data center technicians across multiple sites, including travel for commissioning and complex troubleshooting.

Lead deployment, commissioning, validation, optimization, and production support for large-scale AI and HPC network fabrics. Configure Ethernet and InfiniBand networks, RDMA/RoCE, routing, switching, telemetry, and automation. Conduct acceptance testing, troubleshoot performance and hardware issues, resolve Tier 3 incidents, coordinate vendor escalations, and develop reliability standards, diagnostics, runbooks, and operational handoffs for GPU clusters.

Provides Tier 2 operational support for large-scale GPU compute and storage platforms. Responsibilities include troubleshooting Linux servers, GPU systems, storage services, Kubernetes and Slurm environments; managing incidents and tickets; provisioning and maintaining nodes; coordinating with NOC, SRE, data center technicians, vendors, and Tier 3 teams; supporting upgrades and cluster expansions; documenting issues; and automating recurring operational tasks with Bash or Python.

Lead the integration and production readiness of large-scale GPU clusters, including bare-metal provisioning, Linux and GPU configuration, Kubernetes and Slurm validation, performance benchmarking, acceptance testing, and Tier 3 operational support. Diagnose hardware, firmware, driver, networking, and distributed workload issues; optimize cluster reliability and performance; lead root-cause analysis, vendor escalations, upgrades, automation, documentation, and customer handoff activities.

Coordinate and execute software deployments across staging, testing, and production environments. Build and maintain CI/CD pipelines, automate deployment processes, troubleshoot failures, manage cloud configurations, perform post-deployment testing, and maintain deployment documentation and tooling. Collaborate with development, product, and operations teams to deploy and sustain mission-critical technology in DoD network environments while ensuring security, operational compliance, and deployment readiness.