Top Senior Machine Learning Jobs

Develop and integrate large-scale data applications using Accumulo, Hadoop, Kafka, Spark, Yarn, Python, and JavaScript. Implement predictive analytics, graph algorithms, and machine learning models; design client/server systems and integration points; improve development workflows and support analytic toolchains for Intelligence Community missions.

Design, prototype, and ship LLM- and agent-powered AI features for observability. Rapidly iterate with real users, integrate AI workflows with tooling and alerting, collaborate cross-functionally, and ensure scalable, production-ready solutions in cloud-native environments.

Lead ML research to prioritize and deliver operational models using multimodal atmospheric, radar, satellite, and in‑cloud data. Build datasets, baselines, uncertainty-aware evaluations, and prototypes that meteorologists and engineers can productionize. Work directly with domain scientists, run experiments, and turn results into operational improvements for cloud‑seeding and related forecasting tasks.

Lead ML technical strategy for Live Ads, designing and deploying forecasting, targeting, bidding, auction, and yield-optimization models. Build and evaluate large-scale production ML systems, create online/offline evaluation frameworks, partner with product to set objectives and trade-offs, and communicate results to stakeholders and leadership.

Design, implement, and evaluate alignment and quality metrics for member-facing LLM and recommendation systems. Build tools and pipelines for RLHF, reward modeling, fine-tuning, and human-in-the-loop evaluation. Collaborate cross-functionally, write production-quality code, and improve model robustness and metrics using member feedback and large-scale distributed systems.

Design, build, and operate low-latency, high-QPS ML model serving and feature systems for real-time ad decisioning. Scale inference, ensure online/offline feature consistency, productionize ranking and scoring models, implement monitoring and simulation infrastructure, and partner with Data Science to validate and rollout models safely.

Lead ML initiatives to improve Sales productivity and automation: define roadmap, design and deploy production ML models and AI agents, build measurement pipelines with analytics engineers, iterate from performance and seller feedback, and act as senior technical partner across product, engineering, and Sales to drive measurable revenue impact.

Develop, optimize, and deploy scalable predictive ML models to inform content strategy, valuation, scheduling, and performance. Own end-to-end model lifecycle (feature engineering, training, evaluation, deployment, monitoring) and partner with analytics, data engineering, MLOps, and content teams to scale production solutions and influence ML infrastructure.

Design, build, deploy, and maintain production-grade AI/ML applications (including LLMs and agentic systems). Implement APIs, services, data pipelines, testing, monitoring, and CI/CD. Collaborate with data scientists, platform, security, and product teams to deliver secure, scalable, observable AI solutions that create measurable business value.

Build and productionize ML models for shipping cost estimation, retailer credit underwriting, SEO-driven landing pages, personalization, and lifetime value prediction. Collaborate with data scientists, engineers, and product managers to design features, deploy explainable and performant models, and extract value from two-sided marketplace data to grow and optimize Faire's retailer business.

Deploy and maintain state-of-the-art ML models (LLMs and vision) in production for government customers. Improve models via retraining, tuning, and architecture updates; build scalable ML infrastructure; prototype ML-driven product enhancements; work with massive datasets and multimodal fine-tuning pipelines; collaborate across research, product, and engineering. Requires active security clearance and light travel (~10%).

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Design and optimize machine learning algorithms for sectors like energy and healthcare. Conduct simulations, validate performance, and collaborate with teams.

The Senior Machine Learning Engineer will design innovative machine learning models for drug discovery, leveraging large-scale single-cell datasets and collaborating with ML Scientists to develop optimized models.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

Lead product strategy for AI-powered personalization and recommendation capabilities. Define requirements, partner with Data Science and Engineering to build, test, launch and optimize models, monitor performance, run experiments, prioritize enhancements using analytics, and communicate results to stakeholders while ensuring scalability, compliance and strong customer experiences.

Develop and improve machine learning models for Pinterest's various product surfaces, utilizing deep learning and advanced data processing.

Lead and grow a team building large-scale reinforcement learning and ML behavior models for autonomous driving. Set technical strategy, coordinate with partner teams, oversee training and efficient inference, monitor KPIs, and manage team resources.

Lead the development of machine learning solutions for video personalization, enhancing user experience through data-driven insights and collaboration across teams. Drive technical strategy in building scalable systems and partnerships to innovate customer recommendations.

The Algorithmic Trading Senior Manager at FanDuel will lead the algorithmic trading team, focusing on developing automated trading strategies and optimizing capital utilization while managing risk and team operations.

Design, implement, and deploy machine learning models and systems for recommendations and related problems. Collaborate with engineers, data scientists, and product partners to analyze data, build proofs-of-concept, develop ML/optimization models, write production-quality code, and evaluate models against business goals.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

The Manager, Machine Learning Engineer leads AI/ML initiatives, manages teams, oversees model development, and ensures alignment with business objectives.

Design, implement, and deploy production-scale machine learning models to evaluate disputes, chargebacks, and fraud likelihood. Build and manage orchestration layers for multiple models, collaborate with stakeholders to integrate partner/customer data, and improve automated and supervised decision-making for a product-focused ML environment.

Design and deploy ML models and platforms for Axon products, collaborating with scientists and PMs to build POCs, train/evaluate/test models, enable secure privacy-preserving deployment to cloud and devices, and set standards for ethical AI.