> Markdown version of [/jobs/ext/2282751-python-backend-engineer-ml](https://www.wearedevelopers.com/jobs/ext/2282751-python-backend-engineer-ml). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Python Backend Engineer (ML) - **Company:** APi Group Corporation - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Artificial Neural Networks, Audio Signal Processing, Unit Testing, Microsoft Azure, Amazon DynamoDB, FFmpeg, Python (Programming Language), Machine Learning, Azure Machine Learning, WebSocket, Circleci, Large Language Models, Model Validation, Backend, Integration Tests, Machine Learning Operations, Functional Programming, Cloudwatch, Api Gateway, Terraform, Stream Processing, Grpc, Serverless Computing, Docker, Microservices - **Published:** August 28, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pfuaq545o1 ## About the Role We are seeking a skilled Python Back-end Engineer to join our team and productize cutting-edge ML/AI models in the Legal domain and audio processing more broadly. This role requires solid Python backend engineering experience and strong Machine Learning experience, with the ability to design, develop, and deploy production-grade ML systems. Part of this role includes speech engineering - prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. LLM AI experience, including agentic flows, LiteLLM, CrewAI, AgentCore, AWS Bedrock, and similar tools, is considered a bonus and is not a must-have requirement., * Experience building and productizing agentic flows and AI-driven solutions * Experience with frameworks and platforms such as CrewAI, AWS Bedrock, AgentCore, LiteLLM * Experience integrating various LLMs into production solutions, including training/finetuning of existing LLM models * Familiarity with LLM orchestration, RAG, prompt pipelines, tool usage, or AI agents. ## Description * Integrate various AI/LLMs into production solutions (including training/finetuning existing models); * Optimize ML models for inference, specifically focusing on GPU acceleration; * Build and maintain CI/CD pipelines (e.g., CircleCI) for deployment, unit testing, and integration testing. * Own and ensure the end-to-end automation testing of deployed models. * Support and extend the company's existing speech solutions (including 3rd-party ASR integrations and self-hosted ML models). * Productize ML/ASR models prepared by the research team (Nо training ASR models from scratch). WHAT YOU WILL BRING TO THE COMPANY: * 4+ years of experience developing, wrapping, optimizing, and deploying modern ML/AI models in production. * Develop/wrap, optimize, and deploy modern ML/ASR models in production environments (ASR, SpeakerID, RoleID, LangID, Acoustic events) * Optimize models for inference, including GPU acceleration * Productize ML models prepared by research teams and integrate them into production systems * Understand model evaluation, performance trade-offs, and production monitoring * Strong experience with Python backend development * Build production-grade backend services, APIs, and microservices around ML models * Experience with Python, Docker, gRPC, websockets, and microservices * Build reliable, maintainable, and testable backend components * Integrate ML services into larger production systems * Experience with a cloud provider (AWS/GCP/Azure - we work with AWS) * Work across multiple accounts/regions. ECR, EC2, ECS, CloudWatch. * Deploy API Gateway, DynamoDB, Lambda and other resources via serverless and terraform across environments * Build and maintain CI/CD pipelines (e.g. CircleCI or others) for deployment, unit testing, and integration testing. * Ensure end-to-end automation testing of deployed models., *Prior ASR/speech experience is not a must - but since this will be part of the job, a genuine willingness to learn and grow into this domain is essential. In this area you will: * Support and extend our existing speech solutions, including 3rd party ASR integrations and self-hosted ML models (end-to-end neural networks, NVIDIA Nemo ASR models, speaker feature extractors, LangID, acoustic events models, etc.) * Productize ML/ASR models prepared by our research team (training ASR models from scratch is not required). * Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions) * Perform audio signal processing, working with audio files, audio streams, and audio buffers using tools like FFmpeg and other audio-processing toolkits. * Measure and improve key ASR and SpeakerID metrics such as WER, latency, F1 score, EER, and DER. ## Related Videos - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [AI vs Recruiters and Applicants, Turmoil in the Games Industry, What to Put on a CV](https://www.wearedevelopers.com/videos/1363-ai-vs-recruiters-and-applicants-turmoil-in-the-games-industry-what-to-put-on-a-cv) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Exploring the Power of gRPC-Gateway for Writing RESTful Services](https://www.wearedevelopers.com/videos/2072-exploring-the-power-of-grpc-gateway-for-writing-restful-services) - [Three years of putting LLMs into Software - Lessons learned](https://www.wearedevelopers.com/videos/1508-three-years-of-putting-llms-into-software-lessons-learned) - [Agents, Version Control and Bunnies - Daniel Siegl & David Payr](https://www.wearedevelopers.com/videos/1897-agents-version-control-and-bunnies-daniel-siegl-david-payr) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Dev Digest 210: AI Agents Are Go! 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