Top AI & Machine Learning Jobs

Support engineering by building and maintaining Copilot Studio agents, designing conversation flows, connecting agents to business systems, creating knowledge sources, testing and monitoring agent performance, automating workflows with Power Platform and scripting, and maintaining documentation and data management tasks.

Use specialized tools to visualize, review, and label automotive sensor data for ADAS and autonomous driving. Prepare high-quality datasets for training, calibration, and validation of perception algorithms, collaborate with cross-functional teams, and ensure data accuracy to improve AI and computer vision systems.

Designs, builds, and operates enterprise AI/ML platforms and production services. Responsibilities include infrastructure-as-code, MLOps and CI/CD pipelines, model deployment, API and data integrations, observability, performance optimization, security, disaster recovery, and model-drift monitoring. The role develops reusable code, implements RAG and agentic workflows, and collaborates with architecture, data science, DevOps, security, and product teams while documenting systems and communicating technical concepts to stakeholders.

Develop and improve computer vision and machine learning solutions for industrial applications, including defect detection, 3D reconstruction, quality assurance, and process optimization. Analyze and present data, build cloud-based data and ML pipelines, participate in software development, and test solutions. The role requires strong Python skills, familiarity with TensorFlow or PyTorch, and current university enrollment in an engineering, computer science, mathematics, or science program.

Deploys and optimizes autonomous-driving perception models on embedded automotive platforms. Responsibilities include model conversion, quantization, pruning, knowledge distillation, edge inference optimization, and analysis of CPU, NPU, DSP, and GPU resources. The role also provides optimization recommendations for models, post-processing, and sensor-fusion modules. Candidates need strong Python and C++ skills, perception-model expertise, automotive deployment experience, and preferably mass-production project experience.

Lead development and deployment of machine learning models and data pipelines to optimize manufacturing processes, predictive maintenance, and quality. Analyze large-scale MES/ERP/IoT data, build dashboards, run experiments, and integrate analytics into production. Mentor junior staff, ensure data governance and collaborate with cross-functional teams to drive continuous improvement and digital transformation in the plant.

Hands-on internship to analyze real-world datasets, perform ETL and data analysis, support AI/ML model development, build and improve full‑stack web applications and APIs, create dashboards/visualizations, and debug/test systems.

Lead design and implementation of ML tools for scenario classification, anomaly detection, sensor data quality, behavior analytics, and automated reporting. Build scalable pipelines and automated data curation for camera, radar, and LiDAR; create SIL/HIL replay interfaces, ground-truthing and annotation tools, and offline benchmarking. Integrate ML modules into simulation, HIL/SIL, and CI/CD ecosystems, implement reproducible workflows (Docker, CI/CD, artifact versioning, automated tests), monitor model/data quality and mentor junior engineers while collaborating with verification and perception teams.

Research intern to design, implement, and evaluate task and motion planning and AI algorithms for articulated manipulation. Develop and test deep learning/Gen-AI models, create case studies, implement software, define evaluation criteria, and present technical results under mentorship.

Lead design, development, and deployment of AI/ML solutions for manufacturing: create models for optimization, predictive maintenance, quality analytics; build data pipelines, scalable architectures; apply computer vision, NLP, and time-series methods; integrate with production teams; mentor engineers and drive Industry 4.0 initiatives.