Top Data & Analytics Jobs

As a Senior Machine Learning Engineer, you'll design and deploy AI systems, collaborate on advanced projects, mentor team members, manage infrastructure, and innovate solutions for compliance-focused industries.

As a Senior Data Scientist, you will develop models to extract insights from complex datasets, focusing on temporal and geospatial features, while collaborating with engineering teams to implement solutions.

Intern will contribute to data science and analytics projects, developing data pipelines, supporting AI/ML use cases, and creating visualizations while gaining real-world experience.

The Senior Data Science Workbench Analyst leads automation and cloud optimization projects, enhances data accessibility, mentors junior engineers, and improves security for AI/ML workflows.

Lead the design, development, and integration of AI/ML architectures and systems, mentor junior engineers, and ensure compliance with industry standards.

As a Senior Geospatial Machine Learning Engineer, you will develop and improve algorithms for vegetation analysis, enhance existing products, and lead projects impacting wildfire risk management.

Develop and implement machine learning models to optimize data spend, focusing on improvement of business processes using anomaly detection and forecasting.

The Solution Innovation Architect will design AI/ML demos, collaborate with teams, provide technical expertise, and lead advancements in AI/ML.

The Applied ML Scientist will collaborate with researchers to develop and improve statistical methods that enhance trading strategies through applied machine learning.

As a Machine Learning/Data Scientist, you'll propose solutions to complex scientific problems, collaborate on a long-term roadmap, and work with engineering for production deployment.

Join the Machine Learning team to develop deep learning models for trading strategies, collaborate with researchers and engineers, and mentor new colleagues.

The Machine Learning Engineer will develop machine learning models, optimize processes, and collaborate with engineers to enhance data analysis and automation.

The Machine Learning Engineer will develop and deploy machine learning models, collaborate with teams, and contribute to experimental designs and product requirements.

This role focuses on designing and deploying AI/ML models for federal use cases, supporting model lifecycle management, and advising on ethical AI practices.

Lead the Generative AI team at Xometry, developing and optimizing AI-driven solutions, mentoring team members, and enhancing machine learning capabilities.

Lead the Generative AI team by providing technical direction, developing AI-driven solutions, mentoring team members, and deploying generative models for document processing.

Lead hands-on technical leadership in machine learning engineering, mentor peers, oversee infrastructure delivery, and foster innovation in AI/ML solutions at Xometry.

Lead the Generative AI team at Xometry, focusing on developing and optimizing AI-driven solutions, generative models, and multimodal data processing.

Lead the Generative AI team to advance ML and generative AI capabilities. Develop and deploy models for document processing and mentor team members.

Develop advanced generative models and reinforcement learning algorithms to optimize designs enhancing ecological processes bridging human and natural environments.

The Senior AI/ML Engineer designs and implements AI/ML solutions to enhance profitability, while collaborating across teams and communicating insights to business leaders.

Develop and implement machine learning models, optimize algorithms, analyze data trends, and collaborate with cross-functional teams to enhance the platform.

The Machine Learning Engineer develops AI solutions for cancer care using expertise in ML algorithms and genomic data, collaborating across teams.

The role involves owning an LLM safety domain, generating synthetic data, training LLMs, conducting benchmarking, and developing techniques for safer models. Co-author research papers with the team.

Develop and optimize ML algorithms for fraud detection, risk modeling, and personalized experiences by leveraging large datasets and modern modeling techniques. Collaborate with engineering teams for deployment and monitoring.