yoinka

Senior Data & AI Engineer

Philips

BangaloreSenior
Sign in to applyVerified 2h ago
Location
Bangalore
Work model
On-Site
Level
Senior
Posted
10h ago

Skills

AWSAgileAirflowCI/CDComputer VisionDatabricksDatadogElasticsearchGrafanaKubernetesMLOpsMachine LearningPrometheusPyTorchPythonSplunkTensorFlow

About this role

Job Title Senior Data & AI Engineer Job Description Job Title   Sr. Data & AI Engineer     Job Description   In this role, you   will   join   a   leading innovator in image-guided therapy solutions as   a   Senior AI Engineer for the Azurion   Eye   proposition ,   an integrated AI-enabled clinical platform. You will   develop   state-of-the- art   AI models   using   live camera   feed . Your work will   start with   proving product concepts   during the   Advance Development (AD) phase and productizing   validated concepts into   a   robust,   well-formed   product   solutions .   You will be part of   the Image Guided Therapy Systems business unit with development sites in the Netherlands, China and India. This business unit is responsible for marketing, service, development and manufacturing of solutions and products used in minimally invasive procedures. You will join the global R&D department.   Key areas of responsibility   Design, develop, train and validate computer-vision models.   Implement multi-class object-detection and tracking solutions using CNN-based and modern deep-learning architectures (e.g. YOLO, ResNet, EfficientDet).   Deploy machine learning models using cutting-edge technologies such as Databricks, AWS, and Kubernetes.   Work with AWS and Bedrock for scalable AI solutions.   Implement and manage robust MLOps pipelines for continuous integration, delivery, and monitoring of AI solutions.   Automate model versioning, deployment, and rollback using tools like MLflow, Airflow, and ClearML.   Collaborate with the System Engineer and Data Analytics team to define data schemas, annotation guidelines and ground-truth labelling strategies.   Optimize   models for inference performance on both edge and cloud infrastructure, ensuring real-time throughput requirements are met.   Ensure models meet explainability, clinical safety and regulatory expectations, supporting transition from AD to PDLM production.   Integrate advanced observability solutions (e.g., DataDog, Prometheus, Splunk, Dynatrace, Elasticsearch, Grafana) for real-time monitoring of model and system health.   Build centralized dashboards to track AI/ML metrics, resource utilization, and user impact across environments.   Actively participate in agile ceremonies, code reviews and technical knowledge-sharing within the team.   Author   product   technical documentation, model cards and reproducible training pipeline artefacts.     To succeed in this role, you should have the following skills and experience   15+ years of hands-on experience developing and deploying computer-vision or imaging-AI models ,   AI engineering, and cloud-based solution deployment.   Bachelor’s or master’s   degree in computer science , Machine Learning, Data Science, Artificial Intelligence, or a related field.   Computer vision – strong experience with image classification, object detection and real-time visual tracking pipelines.   Strong expertise in MLOps best practices, model lifecycle management, and production-grade AI/ML systems.   Imaging AI – proficiency in designing and training CNN-based architectures (YOLO, ResNet, EfficientDet, Faster R-CNN, etc.) for multi-class detection tasks.   Python – expert-level programming for ML model development, data engineering and pipeline automation.   P ractical experience training, fine-tuning and deploying deep-learning models   using   PyTorch   or TensorFlow   Proficiency in leveraging AI-assisted development tools to accelerate design, coding, testing and documentation with high-quality outcomes.   Thrives in an agile, entrepreneurial, start‑up–like environment with strong ownership, a learning mindset and the drive to rapidly iterate, validate and deliver customer-centric solutions.   Audio signal processing – ability to complement camera-based vision models with audio-based event cues (nice to have).   Our leadership & ways of working

Listing verified 2h ago. Applications go through the company's official careers site.

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