Top Machine Learning Jobs

Design, implement, and productionize scalable ML models and microservices; build and maintain data pipelines; prototype solutions, participate in architecture and design reviews, and collaborate with cross-functional teams to deliver ML-powered product features.

Perform data and computer science analysis to support customer operations using advanced machine learning, statistical methods, and programming (Python, Java, C/C++). Curate and process large, messy national agency datasets, build models and inferences, translate mission requirements into technical solutions, and communicate results across teams. TS/SCI with polygraph clearance required.

Support maintenance and curation of geospatial data holdings, perform ETL and statistical analysis, build visualizations and lightweight analytic tools, automate preprocessing workflows, monitor data pipelines, and advise on imagery exploitation strategies to improve ML model development.

As an AI and Machine Learning Intern, you will provide software design support, develop AI/ML systems, analyze data trends, and create dashboards while ensuring project requirements and data accuracy.

Develop machine learning and computer vision algorithms for automation and autonomy. Collaborate with experts, optimize solutions, and apply research insights.

As a Senior ML Engineer, you'll design, develop, and deploy ML models for product features, collaborate with teams, and drive research initiatives.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

Design, implement, and support AI/ML systems, working with business units to optimize workflows and educate staff. Communicate findings to stakeholders and ensure compliance with policies.

Interns will work on data innovation projects involving data analysis, machine learning pipelines, AI systems deployment, and enterprise AI integration while gaining exposure to Fortune 500 clients.

The AI/ML Engineer will design and deploy machine learning solutions, build model architectures, collaborate with teams, and ensure model performance and scalability.

The Principal AI/Machine Learning Engineer will lead the adoption of AI/ML in manufacturing by defining use cases, driving implementation, and ensuring organizational readiness.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Develop and productionize ML models for assessing autonomous vehicle behavior, build ML infrastructure, and collaborate across teams for deployment.

The Senior Principal Engineer will lead the development of ML systems at SoundCloud, focusing on recommendation and personalization techniques while mentoring engineers and driving strategic direction.

Lead design and production deployment of ML models focused on pricing, availability, forecasting, and optimization. Build data infrastructure, governance, testing/monitoring, and dashboards. Partner with executives and cross-functional teams, mentor others, and establish scalable data-science practices and experimentation frameworks.

Lead development of auction and bidding algorithms for Microsoft Advertising: design and implement bidding strategies and auction mechanisms, run large-scale experiments, build automation and marketplace optimization systems, and develop causal and ML models to improve advertiser ROI and long-term marketplace health.

Postdoctoral researcher to support P50 analyses using AI and machine learning applied to human brain MRI. Responsibilities include MRI data acquisition and analysis, statistical analyses, model development, and collaboration on projects; experience with stroke and federated learning is a plus.

Design, prototype, and implement quantitative models and data-driven trading analytics using statistics, machine learning/AI, and time series forecasting. Develop code, product specs, and processes; collaborate with Global Markets stakeholders and tech teams; rigorously test model efficacy and deliver polished presentations to drive adoption.

Lead and grow a team of ML researchers and engineers to define strategy and roadmap for next-generation recommendation systems. Translate cutting-edge research into production systems, collaborate cross-functionally, mentor talent, and drive metrics-backed product outcomes using state-of-the-art ML and generative techniques.

Lead research and development of auction mechanism design for online advertising. Evaluate and improve ranking/pricing algorithms, run large-scale experiments (A/B), build data pipelines and production software, apply ML/RL and optimization, and collaborate cross-functionally to deliver measurable business impact.

Develop, deploy, and operate distributed research software and transition prototypes to production using OpenShift/OpenStack and other open-source tools. Collaborate with researchers to design, train, and optimize AI/ML models (including LLMs), contribute to open-source projects, and support student-focused activities like hackathons and mentoring.

Lead integration of state-of-the-art AI/ML into Netflixs content platform and publishing tools. Build roadmaps, incubate ML systems from idea to production, partner with researchers and engineers, automate promotional asset creation, optimize distribution and localization, and measure impact with data-driven evaluation.

Lead development and deployment of cutting-edge ML models for pricing, design and analyze experiments, collaborate with product and engineering, present findings to stakeholders, and lead technical projects to influence team output and business metrics.

Train and iterate custom ML models on manufacturing and design data to estimate cost and complexity, generate designs, and extract structured data from engineering documents. Build end-to-end pipelines from data cleaning and labeling through training, evaluation, and deployment. Collaborate with engineering and manufacturing teams to source datasets and identify opportunities to improve workflows with custom models.

Design, evaluate, and productionize decisioning systems that affect pricing, offers, and routing. Run experiments, build models/heuristics and optimization logic under operational constraints, create feedback loops linking model behavior to business outcomes, and partner with engineers to ship improvements. Use AI as an active tool and help the team adopt AI-native workflows.