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Lead .Net Developer with 10+ years of experience to lead development using .Net, React Native, and JavaScript. The role involves system and cloud design on AWS, utilizing AI tools like GitHub Co-pilot, and requires 4-5 years of AWS experience.
Full-stack developer building applications with Angular, React, and Node.js. Core responsibilities include backend development with Kafka, managing AWS infrastructure (Lambda, S3, DynamoDB), and automating deployments via CI/CD pipelines.
Contract iOS developer role (1-2 years, possible FTE conversion) serving as the technical anchor for an iOS team — 80% coding, 20% architecture. Core work spans Swift with strict concurrency, hybrid SwiftUI/UIKit UI, local-first SwiftData/Core Data design, and setting up AI workflows and MCP server integrations.
An iOS engineer who designs, builds, and maintains native iOS applications for the latest Apple devices — collaborating with the design team on new features, fixing bottlenecks, maintaining core code, and shipping App Store updates. Core stack is Objective-C, Swift, SwiftUI, and Xcode; this is an on-site W2 contract role in Charlotte, NC.
Python Integration Developer for a 6-month contract focusing on Wall Street Office (WSO) integration with MongoDB-backed services. The role involves building adapters, Kafka integrations, and data mappings for loan and credit workflows using Python, SQL, and MongoDB.
Senior Python Developer designing and maintaining ETL pipelines and data integrations for finance and logistics operations. The role involves building RESTful APIs and managing data workflows across warehousing and distribution systems using Python and SQL.
A senior specialist (7-11 years) role in Pennington, NJ designing and developing native iOS applications with Swift/Objective-C alongside Java backend services and RESTful APIs. The engineer leads development, mentors juniors, enforces code quality, and works in Agile teams.
A software engineer (Data) joins the internal AI platform team of a $9.3B AUM private credit investment firm, working fully onsite in Midtown Manhattan. They own and extend production LLM systems — investment memo generation, DDQ automation, and RAG over financial documents — plus agent infrastructure, using Python/TypeScript/Rust/Go and AI-assisted dev tools like Claude Code and Cursor.
Design, develop, and maintain scalable Node.js backend services and RESTful APIs, building microservices and integrating third-party APIs in collaboration with frontend, DevOps, and product teams. Core stack: Node.js/TypeScript, Express.js or NestJS, cloud platforms (AWS/Azure/GCP), Docker, and CI/CD pipelines.
Fully remote contractor role (~15 hrs/week, $30–$100/hr, output-based pay) where you create realistic backend coding tasks and deterministic verifiers to help train next-generation AI systems. Requires strong backend experience (Java, Node.js, Go, Rust, TypeScript, Python, C++), a track record building scalable services and APIs, plus debugging, performance, and automated testing skills.
Contract senior mobile engineers create challenging mobile coding tasks (bug fixes, features, refactoring, performance) with reproducible environments and reference solutions to train frontier AI models. Fully remote across 55 countries, ~15 hrs/week, paid per task at $50–$100/hr using TypeScript/JavaScript, Dart, Swift, or Kotlin.
Software engineer on Amazon Annapurna Labs' new NYC team building AI agents, tools, and models that accelerate customer adoption of AWS Neuron, the software stack for Amazon's Trainium/Inferentia ML chips. Day to day: design, build, test, and deploy agent tooling alongside compiler, hardware, and ML engineers to port and optimize ML workloads.
Software engineer on the AWS Neuron compiler team, building and optimizing the compiler that transforms ML models from frameworks like PyTorch, TensorFlow, and JAX to run on Amazon's custom Inferentia and Trainium AI chips. Daily work centers on C++ compiler optimization passes, tools like MLIR/OpenXLA/StableHLO, and partnering with chip architects and ML teams.
Software engineer on the Neuron Runtime team at Annapurna Labs (AWS) building and maintaining high-performance C++ runtime libraries, drivers, and a profiler for AWS Inferentia and Trainium ML accelerator chips, supporting frameworks like PyTorch, JAX, and XLA, and operating distributed services on AWS.
Principal embedded software/firmware engineer at Raytheon developing motor-control firmware for missile actuation systems (steering, thrust vectoring, stabilization). Day to day: specify, design, verify, and integrate C/C++ digital control algorithms using MATLAB/Simulink, hands-on lab testing, in an onsite role requiring U.S. citizenship and a DoD Secret clearance.
Senior firmware engineer on AWS's BIOS Engineering team designs and maintains UEFI/BIOS firmware for custom x86 and ARM64 server platforms - secure boot, ACPI, boot-time optimization, and board bring-up - while mentoring engineers and coordinating with ODMs and silicon vendors. Debugging uses tools like JTAG and ITP.
Senior SDE on Amazon's AWS EC2 Nitro team, building virtualized, hardware-accelerated local storage for EC2 disk instances at global scale. The role spans the full stack, from low-level hardware/firmware optimization to high-level frameworks, using C, C++, Java, or Rust in Linux environments.
Raytheon is hiring a senior embedded software/firmware engineer to specify, design, verify, and integrate motor-control firmware in C/C++ for precision missile actuation systems. This onsite role (Tucson, Huntsville, or Portsmouth) requires U.S. citizenship, a Secret clearance, and skills in embedded C/C++, MATLAB/Simulink, and hardware integration.
Teaching-track faculty position (open rank) at the University of Chicago's Data Science Institute: teach an average of two data science courses per quarter across fall, winter, and spring, hold regular office hours, and contribute to non-classroom instructional duties. Focus areas span data science, AI/ML, statistics, and computing education.
Systems software engineer on Annapurna Labs' (AWS) ML Server Software team, writing C/C++/Python/Lua to initialize, monitor, debug, test, and qualify ML acceleration servers — working on chip bring-up, device drivers, and hardware interfaces like PCIe, SPI, and I2C, integrating server components into EC2.
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