Top Machine Learning Jobs

Lead design, development, evaluation, and deployment of scalable AI/ML models for insurance use cases. Analyze large datasets, monitor model performance, collaborate with data scientists and engineers, and communicate results to non-technical stakeholders. Ensure models meet statistical, regulatory, and business requirements.

The Senior Python Engineer designs, develops, and deploys machine learning solutions, ensuring scalability and integration into production systems, while collaborating with engineering and data teams.

As a Staff ML Software Engineer, you will lead the development and deployment of machine learning applications, leveraging your expertise to drive software architecture decisions, maintain cloud infrastructure, and collaborate within a small, agile team focused on geospatial challenges related to climate change.

Develop and integrate AI solutions for government customers, focusing on machine learning and deep learning technologies. Collaborate with teams and mentor juniors while providing technical reports.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

Lead ML/AI analytics across STARZ telemetry and operational data to detect anomalies, forecast trends, and surface actionable signals. Build repeatable signals frameworks, apply anomaly detection/classification/clustering/time-series models, leverage generative AI/LLMs for summarization and RCA, define alerting and escalation, partner with engineering and product, and mentor junior analysts.

The role involves developing advanced machine learning algorithms, solving complex optimization problems using reinforcement learning techniques, and leading technical projects while optimizing solutions for operational efficiency.

Develop, iterate, and deploy machine learning models and agent systems for investment decision-making. Design experiments, build reproducible feature-generation and evaluation workflows, and work with large-scale financial and alternative datasets to identify predictive signals and improve production performance.

Work with strategic customers to identify high-leverage ML opportunities, build production-grade solutions, design adaptive data strategies, deploy models, and own outcomes from discovery through deployment.

Develop AI/ML models for 3D simulation and geology prediction, refine data pipelines, and integrate deep learning tech with product backend.

As a Senior Machine Learning Engineer, you will architect a scalable ML platform, collaborate across teams, and ensure best practices for ML workflows and operations.

Lead the Machine Learning strategy at Gather AI, focusing on computer vision, building teams, and enhancing ML systems for warehouse intelligence.

Design and deploy ML models and platforms for Axon products. Collaborate with scientists and PMs to build POCs, implement training techniques, enable secure privacy-preserving model improvements, and accelerate research-to-production pipelines.

Lead ML work for send-time, channel, and propensity optimization to increase engagement. Design and ship recommendation/sequential-decision systems, ensure experimental rigor, own production models end-to-end, and mentor a small ML team while partnering with product, engineering, and growth.

The Machine Learning Scientist will build and integrate ML models, analyze data, design scalable pipelines, and ensure robust model testing.

Seeking a Senior Data Scientist/ML Engineer to develop and deploy Machine Learning algorithms, collaborate with teams, and assist federal clients in their digital transformation.

Design, build, deploy, and operate scalable production ML and AI systems (batch and real-time) to predict KPIs and optimize provider network operations. Own end-to-end model lifecycle including feature engineering, training, deployment, monitoring, CI/CD, and experiment tracking. Collaborate with product, engineering, clinical and business stakeholders, implement production-quality code (Python, Spark, SQL), and integrate LLMs, RAG, and other AI capabilities to deliver measurable business and clinical outcomes.

As a Senior ML Engineer, you will develop ML pipelines, work with language models, and build agentic AI systems while implementing MLOps practices.

The Senior Machine Learning Engineer will develop end-to-end ML systems connecting perception inputs to driving behavior, enhance model performance, and mentor juniors.

Develop, deploy, and monitor machine learning and analytic capabilities for defensive cyber operations. Ingest and transform multi-source data, build data pipelines, validate operational models, collaborate with analysts to deliver actionable insights, and document processes for reproducibility in high-security environments.

As a ML Engineer at Wispr, you will design features for a voice interface, optimize ML inference, and scale personalization of speech models.

Design, implement, train, validate, and deploy machine learning models at enterprise scale. Collaborate with data engineers and software engineers to preprocess data, perform feature engineering, evaluate model performance, and integrate models into production. Continuously improve models and adopt new ML and cloud data tools to solve business problems.

The role involves designing scalable distributed systems using Scala, enhancing feature stores for performance, and collaborating with ML engineers to resolve challenges.

Designs, implements, and deploys scalable AI/ML solutions: selects algorithms, engineers features, trains and tunes models, integrates models into production, monitors performance, mentors team members, leads design reviews, and communicates technical strategy to stakeholders.