Top Senior Machine Learning Jobs

As a Machine Learning Engineer, you'll build and enhance features for a search stack, design ML/NLP solutions, and implement an experimentation framework while ensuring code quality.

The Founding ML Engineer will develop and deploy ML systems, collaborate with teams, and translate ambiguous problems into production ML solutions, shifting between client delivery and platform development.

Design, develop, implement, and monitor statistical and machine learning models to support credit risk, collections, servicing, marketing, and forecasting. Build data pipelines, translate business needs into analytical solutions, support model governance, testing, deployment, and ongoing performance monitoring, and communicate results to stakeholders.

Lead development and deployment of predictive and ML models for credit risk, collections, and operations. Mentor data scientists, promote MLOps and modern tools, present insights to stakeholders, and drive experimentation with techniques such as causal inference and GenAI.

The Senior Applied Scientist will develop machine learning solutions for personalization, pricing optimization, and fraud detection, leading model development and experimentation while collaborating with various teams.

The Senior Machine Learning Engineer will design, deploy, and mentor on ML models, collaborate with customers, and influence product direction. Responsible for robust ML systems and data pipelines.

As a Senior Machine Learning Engineer, you will own the ML stack, develop generation systems, improve quality, collaborate cross-functionally, and build data pipelines.

The Applied ML Engineer will research and build AI/ML systems, own model development, partner with teams to impact marketplace metrics, and establish best practices for AI/ML at Paraform.

The Machine Learning Engineer role at Wayve focuses on leading initiatives in model-based autonomous driving, involving the development and delivery of ML-driven behaviors, collaboration across teams, and mentoring other engineers.

Partner with customers to design and deliver production-ready AI/ML solutions, drive POC-to-production success, troubleshoot technical issues, inform product roadmap with customer feedback, and communicate outcomes to stakeholders.

The Staff Machine Learning Engineer will design and implement ML systems, build scalable architectures, collaborate with data teams, and drive technical strategy for AI applications.

The Staff Machine Learning Engineer will optimize the inference layer for voice applications, focusing on model serving and real-time audio processing. Responsibilities include driving performance architecture, collaborating with model partners, and developing evaluation frameworks for STT and TTS models.

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.

Lead end-to-end machine learning solutions for League of Legends, from problem framing to production. Build personalization, recommender, matchmaking, and in-game ML systems; design evaluations and experiments; integrate models with game and service engineering; create reusable ML patterns; mentor engineers and improve ML observability, monitoring, and launch practices.

The Senior ML Engineer will architect data pipelines, develop classification algorithms, manage data integration, and mentor team members in a cross-functional setting.

The Senior Engineer II, Machine Learning will develop and implement machine learning models, analyze multiomic/single-cell data, and apply image processing techniques for research projects.

Architect and own the ML roadmap for continental-scale grid intelligence. Design and deploy multimodal ML, GNNs, physics-informed models, and RL for grid planning, simulation, and operations. Mentor senior engineers, set production standards, and collaborate with power-systems scientists and utility partners to deliver scalable, reliable ML systems.

Design, build, and deploy end-to-end machine learning solutions for growth marketing platforms. Develop scalable model training, validation, and serving pipelines, lead experiments, present results to leadership, and mentor junior engineers to improve customer acquisition, retention, and ROAS.

Pioneering machine learning solutions for the defense sector, developing and deploying production-grade ML models, tackling complex data challenges, and collaborating with engineers.

Lead technical vision and development of large-scale, low-latency DNN models for ads conversion. Mine text, visual, and user signals, use LLMs and AI tools to accelerate analysis, automate workflows, and mentor engineers while collaborating on new ad products.

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 technical direction for autonomous mineral refining by designing, validating, and deploying RL-based control models. Own autonomy roadmap, set simulator and modeling standards, solve sim-to-real and non-stationarity problems, partner with domain experts and leadership on techno-economic decisions, and mentor engineers while delivering production ML that runs on live plant equipment.

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.