Machine Learning Engineer

• Lead the design and development of advanced machine learning models specifically tailored for autonomous vehicles utilizing deep learning, simulation, and large-scale data analysis
• Deploy scalable and efficient ML models on our autonomous vehicle platform
• Integrate modern technologies with rigorous safety standards while maintaining cost efficiency
• Significantly contribute to development of needed components for end-to-end ML training and deployment, from data strategy to optimization and validation
• Be a champion of the scientific method and critical thinking in inventing state-of-the-art deep learning solutions
• Work in a high-velocity environment and employ agile development practices
• Collaborate closely with teams such as Perception, Motion Planning, Simulation, Infrastructure, and Tooling to drive unified solutions

Senior Machine Learning Engineer, Behavior

• Lead optimization areas in the Ad-Tech domain.
• Utilize data science and machine learning technologies to identify business challenges, develop and implement models, and continuously improve productivity and reliability through iterative enhancements.
• Focus on mid to long-term business goals and impact, propose key issues to be resolved, and prioritize them effectively.
• Employ a data-driven approach to formulate hypotheses, design evaluation strategies, and develop appropriate machine learning models.
• Propose, promote, implement, and validate business improvement plans.
• Develop and maintain machine learning models in the advertising domain, including recommendation systems, matching optimization, and ad classification.
• Apply statistical and data science techniques to uncover product insights and drive optimization based on business logic.
• Enhance the performance of advanced machine learning models by leveraging embeddings for images and text.
• Design time-series models to evaluate advertising effectiveness and optimize advertising budget strategies.

Ad Tech Engineer, Machine Learning Engineer – Marketplace

Computer Vision Engineer

• Driving development as a technical lead for the Computer Vision component in one or multiple projects, including responsibility for requirements management, schedule management, and task management
• Perform software verification, integration, and release management on target hardware
• Engage in mission system validation and real-time operational support

シニアコンピュータービジョンエンジニア / Senior Computer Vision Engineer

AI Engineer

• Design, implement, and enhance ML-based driver workload (busyness) estimation algorithms that take vehicle CAN signals, various in-vehicle sensors, and driver operation logs as time-series inputs
• Build and operate training data infrastructure and evaluation pipelines, including label and annotation policy design, data preprocessing, and feature engineering
• Investigate and improve logics that combine CAN-based workload indicators with other workload measures, such as surrounding-vehicle information and image/vision-based indicators
• Design interfaces and specifications to feed workload estimation results into driving suggestion and voice prompt logic, and continuously improve overall feature performance
• Collaborate with software engineers, test engineers, UX members, and other stakeholders to align on requirements and evaluation metrics, and to organize and share experiment results and technical learnings
• Participate, as required by projects and business needs, in planning and conducting evaluations using simulators and on-road test vehicles (including business trips), and drive improvement cycles based on real-world findings

Driver Workload Estimation AI Engineer, Info Mobility

• Develop and Optimize ML Models: Design, build, and optimize machine learning models to solve complex problems and perform specific tasks. Focus on optimizing model performance and scalability to handle large-scale production systems.
• Feature Engineering: Conduct in-depth feature engineering to improve the robustness and accuracy of ML models, particularly in the context of natural language processing (NLP), computer vision, and multimodal learning.
• Model Deployment and Integration: Collaborate with cross-functional teams to integrate ML solutions into existing products and services, ensuring seamless deployment and operational efficiency.
• Research and Innovation: Keep up-to-date with the latest research and advancements in AI and machine learning, and related fields such as NLP and computer vision.
• Engineering Infrastructure: Design engineering infrastructure to support machine learning systems at scale.
• Experimentation and Testing: Conduct A/B testing, experiments, and evaluations to assess the performance and impact of ML models, using insights to inform further iterations and improvements.

Machine Learning Engineer – AI, LLM

• Responsible for the development of the Power offering.
• Fully dedicated to a new product covering the Japanese power market.
• Adapt and expand existing modelling infrastructure to build fundamental forecasts.
• Learn and adapt existing models to the Japanese market.
• Integrate market signals from other commodities (LNG, coal) to enhance forecast quality.
• Enrich the product and participate in the development of new features.
• Build and improve monitoring and alerting tools and dashboards.
• Ensure good performance on API to distribute data to end users.
• Discuss the roadmap in collaboration with the product team.

Power ML Engineer

• Design and develop scalable LLM-based solutions for human interaction AI systems
• Collect, curate, and prepare datasets for LLM product/services development
• Make technical judgment and architectural decisions while working with cross-functional teams
• Build and optimize ML/LLM pipelines from data ingestion to automated model serving

See all jobs on JobTailor