Senior Engineer - Machine Learning

Core ML EngineerWe are seeking a highly skilled Core ML Engineer to design, develop, and optimize machine learning systems that power next-generation AI platforms and applications. This role focuses on model development, inference optimization, and scalable ML infrastructure, enabling production-grade AI capabilities across enterprise systems.The ideal candidate combines strong software engineering fundamentals with deep ML expertise, and thrives in building robust, high-performance systems at scale.Key ResponsibilitiesCore ML System DevelopmentDesign and implement machine learning models and pipelines for production useBuild scalable training ? evaluation ?

deployment workflowsDevelop reusable ML components, libraries, and frameworksInference & Performance OptimizationOptimize model inference for latency, throughput, and costImplement advanced techniques such as caching, quantization, batching, and routingBenchmark and profile models across diverse workloads and hardware environmentsModel Integration & DeploymentIntegrate ML/LLM models into APIs, microservices, and applicationsBuild and maintain model-serving infrastructure (e.g., vLLM, ONNX, custom runtimes)Collaborate with platform and infrastructure teams for scalable deploymentData & Pipeline EngineeringDesign data pipelines for ingestion, preprocessing, feature engineering, and validationImprove data quality and model reliability through systematic evaluationCross-functional CollaborationPartner with product, platform, and hardware teams to deliver end-to-end ML solutionsParticipate in design reviews and contribute to system architecture decisionsMinimum Qualifications• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field.Preferred QualificationsStrong programming skills in Python and at least one systems language (C++/Rust/Go)Solid understanding of:Machine learning fundamentals (supervised, unsupervised, deep learning)Transformer architectures / LLMsModel evaluation and debuggingExperience with:ML frameworks (PyTorch, TensorFlow)Model deployment and serving systemsBuilding scalable software and APIsExperience with:Large Language Models (LLMs), multimodal models, or generative AIRetrieval systems and RAG pipelinesDistributed computing and GPU/accelerator environments including model serving and efficient cache/state management (e.g.

KV cache, embeddings) across disaggregated systemsKubernetes, Docker, and CI/CD pipelinesAgentic and multi-step AI workflows, tool integration, orchestration, and multi-component pipelinesKnowledge of:Model optimization techniques (quantization, distillation, caching)Vector databases and search systems (OpenSearch, Qdrant, etc.)Cost-aware system design – model routing (small vs. large models), dynamic batching, and caching strategiesPay range and Other Compensation & Benefits: $140,800.00 - $211,200.00