Top AI & Machine Learning Jobs

Productize internal AI prototypes into production-ready, scalable, secure applications. Develop ML/GenAI solutions with LLMs and agentic approaches, build backend APIs, databases and microservices, design cloud infrastructure on Azure/AWS, implement CI/CD and containerization, create frontend UX/UI with modern frameworks, support R&D evaluations, and collaborate with partners. Willingness to travel.

Deploy and optimize autonomous-driving perception models on automotive embedded platforms. Improve on-device inference via model conversion, quantization, pruning, and distillation. Analyze CPU/NPU/DSP/GPU performance and advise optimizations for models, post-processing, and sensor fusion to achieve real-time, high-accuracy edge inference.

Lead development of AI tools for systems engineering, define specifications and test scenarios, evaluate new technologies for R&D, support project planning and coordination, prototype and validate components, and collaborate across engineering and external partners to advance automotive AI and system solutions.

Test and validate AI models and software for automotive use cases: generate ground truth, build annotated datasets and testing frameworks, evaluate technologies, support R&D engineers, coordinate projects and outsourced work, and collaborate with internal and external partners to drive innovation and product readiness.

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.

Develop and optimize classical and deep-learning computer vision algorithms for ADAS using camera feeds. Tasks include detection, segmentation, tracking, image enhancement, model pruning/quantization, dataset analysis, real-time optimization for production ECUs, experiment design, integration with embedded teams, defect root-cause analysis, documentation, and compliance with automotive development processes and KPIs.

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.

Design, build, deploy, and maintain LLM-based applications and AI agents using Azure OpenAI and Cognitive Services. Create secure integrations, ETL pipelines, RAG workflows, and APIs/microservices. Perform prompt engineering, model tuning, monitoring, and DevOps practices. Support production incidents, documentation, and cross-functional collaboration to deliver AI-driven business solutions.

Design and implement AI-enabled automation and testing solutions for HR, Payroll, and Finance using Azure AI and Copilot Studio. Integrate AI into RPA and test frameworks, build data pipelines, connect via REST APIs, apply prompt engineering and model evaluation, and ensure security, observability, and QA across deployments.

Work as an AI-focused intern to develop, train, validate, and deploy machine learning and computer-vision models (YOLO, Python, OpenCV, TensorFlow/PyTorch) for production-floor systems. Collaborate with cross-functional teams to gather requirements, monitor and improve model performance, document methods, report progress, and provide training and support for AI initiatives.