Top Machine Learning Jobs

As a Senior Software Engineer at NVIDIA, you will design and implement inference software optimizations for AI applications using TensorRT, collaborating with deep learning experts to influence hardware and software design.

Optimize training and inference performance of foundation models by writing and tuning CUDA/Triton GPU kernels, profiling and removing bottlenecks, implementing low-precision and mixed-precision strategies, optimizing MoE routing and expert dispatch, integrating high-performance libraries, and collaborating closely with researchers to translate model ideas into scalable, efficient implementations.

Lead design, development, and production deployment of ML models and GenAI/LLM solutions to optimize clinical trial workflows. Build scalable pipelines, monitoring, and CI/CD for robust production use. Collaborate cross-functionally, mentor junior engineers, and communicate technical results to technical and non-technical stakeholders.

As a Machine Learning Engineer I, you will develop and deploy machine learning systems for core relevance signals, collaborating with engineers and product teams.

Develop, analyze, and deploy AI/ML models to support Missile Defense Agency ground test scenario design. Optimize model performance, ensure explainability and reliability, integrate solutions with cross-functional systems, maintain scalable Python code, research emerging AI techniques, and produce technical documentation and briefings for stakeholders.

As an Applied ML Software Engineer, you will design and implement ML models, manage cloud infrastructure, and optimize backend systems for AI-driven content discovery and recommendations.

As a Machine Learning Engineer, you will build models and agents to accelerate scientific discovery, collaborating with researchers and developing efficient infrastructure.

As a Founding Machine Learning Engineer at Trove, you will develop AI applications for financial firms, focusing on data retrieval and knowledge graphs. Your role involves designing algorithms and collaborating with elite AI labs to enhance human-level capabilities in GenAI.

The role involves developing machine learning models for neural data, collaborating with teams, and exploring new architectures. The candidate should have applied ML experience and strong programming skills.

Lead development and deployment of credit, account-management, and fraud ML models using embeddings, transformers, and classical approaches. Own data pipelines, feature engineering from structured and unstructured sources, production monitoring, and cross-team integration while shaping technical strategy and mentoring Juniors.

The Machine Learning Engineer will collaborate on AI projects, develop algorithms, optimize solutions, and maintain coding standards within Kitware, contributing to various machine learning tasks.

Collaborate on machine learning projects, perform prototyping, validate algorithms, and troubleshoot code for robustness in AI and computer vision.

The ML Engineer will design, develop, and implement machine learning models, manage ML pipelines, integrate APIs, and collaborate with teams to deploy solutions.

Design and implement production-grade multi-agent LLM systems and agent workflows for advisor-facing tools. Build distributed, observable services (model serving, vector DBs, RAG) with memory/state management, validation, and compliance. Partner with product and engineering to optimize for latency, cost, and reliability, and establish evaluation frameworks to ensure grounded, auditable AI-driven insights for portfolio and advisor workflows.

The Staff ML Engineer will lead architecture decisions for ML infrastructure, operate real-time computer vision systems, and mentor engineers, ensuring high-quality ML deployment and operational excellence at SimpliSafe.

The Applied Machine Learning Research Scientist will translate ML techniques into scalable systems, improve LLM performance, and optimize workflows while collaborating closely with researchers and engineers.

As a Senior Machine Learning Engineer, you will build and operate scalable ML systems, oversee projects from inception to deployment, and improve system performance while collaborating with cross-functional teams and mentoring junior engineers.

As a Senior Machine Learning Engineer, you will design and operate scalable ML systems for real-time personalization, collaborating with teams and mentoring engineers.

As a Machine Learning Engineer, you'll design and deploy large-scale models for advertising and commerce systems, optimizing for performance and relevance while maintaining ML pipelines.

Lead architect and hands-on developer for embedded AI/ML autonomy across the full lifecycle: model design, optimization for resource-constrained flight hardware, integration with flight software and avionics, V&V and runtime assurance, cross-functional alignment, and customer-facing technical leadership for mission-critical space systems.

Design, develop, and enhance AI/ML software solutions, collaborate with teams, and work with large datasets to support mission operations.

The Machine Learning Engineer II will design, develop, and maintain machine learning models, lead ML initiatives, collaborate across teams, and mentor junior members while working on Insider Risk Management solutions.

As a Lead Machine Learning Engineer, you will operationalize ML models, collaborate with teams, solve complex problems, optimize data pipelines, and implement best practices in ML deployment.

The Applied Scientist will develop and enhance machine learning models, design A/B tests, evaluate performance, and collaborate with stakeholders to enhance decision-making and operational workflows in healthcare.

The Senior Machine Learning Scientist will lead R&D in AI applications, focusing on LLM, CV, and GenAI technologies, collaborating with teams to develop and optimize innovative models and algorithms.