Top Senior Machine Learning Jobs

The AI/ML Engineer will design, develop, and implement scalable AI solutions for a DoD client, requiring expertise in AI/ML technologies and integration with existing systems.

As an AI Specialist SC, you will support major global clients by offering presales machine learning solutions, driving business transformations and technical discussions, while collaborating across teams.

The Specialist Solutions Architect will guide customers in architecting ML & AI applications, provide advanced technical support, and collaborate cross-functionally to enhance Databricks' AI offerings.

Design and build core ML systems for AI agents, managing the lifecycle from problem framing to deployment, ensuring solutions are scalable and enterprise-ready.

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.

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.

Develop and implement AI/ML algorithms across domains (vision, NLP, time series, RL, LLMs). Analyze large multimodal datasets, prototype research, document solutions, support training/deployment pipelines (AWS), and mentor team members.

The role involves designing and refining reward signals for recommendations, collaborating with teams, and implementing ML solutions to enhance user satisfaction.

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.

As a Senior Machine Learning Engineer, you will drive AI initiatives, collaborate across teams, and develop scalable ML infrastructure to improve healthcare.

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

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

The Senior AI/ML Engineer will build scalable AI systems, work with LLMs, optimize models, and deploy solutions using AWS while ensuring ethical standards.

Lead ML projects, guiding technical direction and platform capabilities. Collaborate across teams to deliver production ML systems impacting customers. Advocate for AI-first tools and mentor engineers.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

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

The Machine Learning Engineer will develop secure AI capabilities, collaborate with teams, and build ML systems while evaluating technologies for government sponsors.

The Machine Learning Performance Engineer will build training and inference pipelines, enhance deep learning frameworks, improve performance, and collaborate with researchers and engineers to optimize trading systems.

The Machine Learning Engineer will support research and implementation of algorithms for simulations, develop ML models, and mentor teams while using modern tech practices in an agile environment.

Lead design, build, deploy, and maintain production-grade AI/ML systems (LLMs, agentic architectures, classical ML). Provide hands-on technical leadership across architecture, model selection, implementation, testing, deployment, observability, and operational support while collaborating with data scientists, platform and security teams and mentoring engineers.

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.

Lead development of large-scale ranking, personalization, and recommendation systems for Roku's entertainment assistant. Design and deploy ML models (LLMs, transformers, RL, bandits), build feature platforms and data pipelines, run online A/B experiments, and mentor engineers while balancing engagement, retention, relevance, and monetization objectives.

Research and develop ML and statistical algorithms for networking, edge computing, cybersecurity, and autonomy. Build and evaluate simulation-driven solutions, lead subsystem software development, create automated tests, and contribute to proposals and technical plans while presenting results to customers and senior staff.

Morgan Stanley seeks a Machine Learning Researcher to solve critical problems with innovative research. Responsibilities include applying machine learning techniques and strong communication skills within a collaborative team. Ideal candidates have 4+ years of research experience and proficiency in statistical learning methods.