Prodigy Resources
Overview
We are seeking a Senior AI/ML Systems Engineer to help build the next generation of AI-augmented development infrastructure. This role centers on integrating and orchestrating AI technologiesboth commercial and internally hostedinto our engineering workflows to improve productivity and maintain enterprise-grade quality standards. You will design and implement scalable systems that enable engineers to collaborate effectively with AI, ensuring our platforms are robust, reliable, and future-ready. This is an onsite position requiring regular in-person collaboration at our office. Responsibilities
AI Systems Integration & Orchestration: Integrate AI services from APIs, self-hosted models, and open-source solutions into unified workflows. Build abstraction layers to enable seamless switching between AI providers and models. Design intelligent routing systems for optimal model selection based on performance, cost, and capabilities. Develop testing and validation frameworks for AI-assisted pipelines. Create feedback loops that improve AI tool effectiveness over time. Design scalable architectures to integrate AI across the technology stack. Build middleware and service layers standardizing AI interactions. Develop microservices that allow seamless AI integration. Implement failover and resilience strategies for high availability. Build backend systems in Rust for performance-critical services. Create user-friendly interfaces for engineers to interact with AI tools. Develop APIs using Rust frameworks (Actix-web, Axum, Rocket). Build real-time pipelines for model serving and inference. AI/ML Infrastructure & Operations: Develop and maintain ML pipelines for deployment, monitoring, and lifecycle management. Implement RAG systems and vector databases to enhance contextual AI responses. Build infrastructure to host and serve internal AI models at scale. Establish MLOps practices for reliable deployments and evaluations. Containerize AI services and manage orchestration with Kubernetes. Build CI/CD pipelines with AI-assisted testing and review. Configure auto-scaling for inference workloads. Manage hybrid infrastructure across cloud and on-premise. Implement observability for distributed AI systems. Qualifications
Core Requirements 3+ years of professional experience in Rust (Tokio, async, Rust web frameworks). 4+ years of professional experience in Python (ML frameworks, data processing, APIs). Hands-on experience integrating commercial and self-hosted AI models into production systems. Strong knowledge of Docker, Kubernetes, and cloud-native architectures. Experience building APIs (REST, GraphQL, gRPC) at scale. Preferred Experience Rust web frameworks (Actix-web, Axum, Rocket, Warp). WebAssembly and Rust-based frontend technologies. Vector databases (Qdrant, Pinecone, Weaviate, Milvus). Model serving frameworks (TensorRT, Triton, vLLM). LLM optimization and prompt engineering techniques. Professional Background 5-8 years of software engineering experience with at least 2 years in AI/ML systems integration. Experience architecting enterprise systems balancing innovation, stability, and compliance. Strong track record of deploying and maintaining production platforms at scale. Cross-functional collaboration with data science, engineering, and product teams. Technical leadership including mentorship, setting best practices, and driving architecture decisions. Experience managing high-availability systems with strong SLAs. Key Focus Areas
Evaluating and selecting AI technologies for business use cases. Building developer-friendly platforms that abstract AI complexity. Establishing metrics to measure AIs impact on engineering productivity. Providing documentation, training, and guidance for adoption. AI/ML Platforms:
OpenAI, Anthropic, Google Vertex AI, AWS Bedrock, Hugging Face Frameworks:
PyTorch, TensorFlow, JAX, ONNX Location
This position requires onsite presence. Candidates must be able to commute or relocate. We are committed to diversity and inclusion and encourage applications from individuals of all backgrounds. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries
Software Development Were unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr
We are seeking a Senior AI/ML Systems Engineer to help build the next generation of AI-augmented development infrastructure. This role centers on integrating and orchestrating AI technologiesboth commercial and internally hostedinto our engineering workflows to improve productivity and maintain enterprise-grade quality standards. You will design and implement scalable systems that enable engineers to collaborate effectively with AI, ensuring our platforms are robust, reliable, and future-ready. This is an onsite position requiring regular in-person collaboration at our office. Responsibilities
AI Systems Integration & Orchestration: Integrate AI services from APIs, self-hosted models, and open-source solutions into unified workflows. Build abstraction layers to enable seamless switching between AI providers and models. Design intelligent routing systems for optimal model selection based on performance, cost, and capabilities. Develop testing and validation frameworks for AI-assisted pipelines. Create feedback loops that improve AI tool effectiveness over time. Design scalable architectures to integrate AI across the technology stack. Build middleware and service layers standardizing AI interactions. Develop microservices that allow seamless AI integration. Implement failover and resilience strategies for high availability. Build backend systems in Rust for performance-critical services. Create user-friendly interfaces for engineers to interact with AI tools. Develop APIs using Rust frameworks (Actix-web, Axum, Rocket). Build real-time pipelines for model serving and inference. AI/ML Infrastructure & Operations: Develop and maintain ML pipelines for deployment, monitoring, and lifecycle management. Implement RAG systems and vector databases to enhance contextual AI responses. Build infrastructure to host and serve internal AI models at scale. Establish MLOps practices for reliable deployments and evaluations. Containerize AI services and manage orchestration with Kubernetes. Build CI/CD pipelines with AI-assisted testing and review. Configure auto-scaling for inference workloads. Manage hybrid infrastructure across cloud and on-premise. Implement observability for distributed AI systems. Qualifications
Core Requirements 3+ years of professional experience in Rust (Tokio, async, Rust web frameworks). 4+ years of professional experience in Python (ML frameworks, data processing, APIs). Hands-on experience integrating commercial and self-hosted AI models into production systems. Strong knowledge of Docker, Kubernetes, and cloud-native architectures. Experience building APIs (REST, GraphQL, gRPC) at scale. Preferred Experience Rust web frameworks (Actix-web, Axum, Rocket, Warp). WebAssembly and Rust-based frontend technologies. Vector databases (Qdrant, Pinecone, Weaviate, Milvus). Model serving frameworks (TensorRT, Triton, vLLM). LLM optimization and prompt engineering techniques. Professional Background 5-8 years of software engineering experience with at least 2 years in AI/ML systems integration. Experience architecting enterprise systems balancing innovation, stability, and compliance. Strong track record of deploying and maintaining production platforms at scale. Cross-functional collaboration with data science, engineering, and product teams. Technical leadership including mentorship, setting best practices, and driving architecture decisions. Experience managing high-availability systems with strong SLAs. Key Focus Areas
Evaluating and selecting AI technologies for business use cases. Building developer-friendly platforms that abstract AI complexity. Establishing metrics to measure AIs impact on engineering productivity. Providing documentation, training, and guidance for adoption. AI/ML Platforms:
OpenAI, Anthropic, Google Vertex AI, AWS Bedrock, Hugging Face Frameworks:
PyTorch, TensorFlow, JAX, ONNX Location
This position requires onsite presence. Candidates must be able to commute or relocate. We are committed to diversity and inclusion and encourage applications from individuals of all backgrounds. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries
Software Development Were unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr