Senior AI Engineer ISP & Vision Systems

The Senior AI / ML Engineer – ISP & Vision Systems will design, develop, and deploy production -grade AI solutions for image signal processing (ISP), computer vision, and vision -based systems. This role focuses on applying machine learning, deep learning, and Gen -AI to improve image quality, defect detection, visual analytics, and vision -driven decision systems.

Requirements

Key
Responsibilities

AI Strategy &
Vision Use -Case Development

• Collaborate with
  cross -functional teams and ISP / vision domain experts to identify
  opportunities for AI integration in imaging and vision workflows
  
• Help AI product
  managers and business stakeholders understand the capabilities, limitations,
  and trade -offs of AI in ISP and vision systems
  
• Lead proof -of -concept
  (PoCs) and pilot programs to demonstrate measurable value of AI -based vision
  solutions
  

Data Engineering
& Infrastructure

• Analyze, preprocess,
  and transform large datasets including images, video streams, metadata, logs,
  and sensor data
  
• Design and build data
  ingestion and transformation pipelines for vision datasets
  
• Set up and manage AI
  development and production infrastructure (edge and cloud -based vision systems)
  
• Collaborate with the
  Data Analytics team to integrate large -scale vision data solutions
  

Model Development
& Deployment

• Design, train, and
  deploy AI / ML models for:
  
• Image enhancement and
  restoration
  
• Defect and anomaly
  detection
  
• Object detection,
  tracking, and segmentation
  
• Vision -based analytics
  and automation
  
• Build AI models from
  scratch and apply transfer learning for vision tasks
  
• Identify and curate
  new datasets for training and validation
  
• Deploy models into
  production environments, including embedded and edge devices
  
• Create APIs and
  services to integrate AI outputs into downstream vision and business
  applications
  

Monitoring,
Optimization & Adoption

• Monitor AI and vision
  system performance and continuously improve deployed models
  
• Optimize models for
  latency, accuracy, and resource constraints on edge devices
  
• Provide technical
  documentation, training, and operational support to engineering and production
  teams
  

Research &
Innovation

• Stay current with
  latest AI/ML, computer vision, and ISP advancements
  
• Propose innovative
  AI -driven approaches for ISP pipelines and imaging systems
  
• Participate in
  fast -paced prototyping to explore improvements in vision and imaging workflows
  

Qualifications & Experience

Minimum
Qualifications

• Bachelor’s degree in
  Computer Science, Data Science, Electronics, Imaging, or related field
  
• Strong programming
  skills in Python, C/C++, R, VB.NET, or equivalent
  
• Proficiency with ML
  frameworks such as TensorFlow, PyTorch, scikit -learn
  
• Hands -on experience in
  AI vision, computer vision, or Gen -AI
  
• Experience in
  Full -Stack Development
  
• Experience deploying
  ML models in production vision systems (edge or cloud)
  
• Strong analytical,
  problem -solving, and cross -functional collaboration skills
  
• Excellent verbal and
  written communication skills
  

Preferred
Qualifications

• Strong knowledge of
  ISP pipelines including demosaicing, noise reduction, HDR, color correction,
  and sharpening
  
• Experience with deep
  learning for image classification, segmentation, and object detection
  
• Knowledge of LLMs,
  Prompt Engineering, RAG, and LLM fine -tuning
  
• Experience with model
  explainability, validation, and performance benchmarking in vision systems
  
• Familiarity with
  camera sensors, optics, and imaging hardware
  
• Experience working
  with image/video datasets, metadata, and vision telemetry
  

Added Advantage

• Knowledge of ISP
  tuning, camera calibration, and image quality evaluation
  
• Understanding of
  sensors, drivers, Video and camera control pipelines
  
• Experience with data
  processing and streaming tools:
  
• Kafka
  
• Spark            
  
• Apache NiFi
  
• Dataiku
  
• Familiarity with NoSQL
  and distributed storage systems:
  
• Cassandra
  
• MongoDB
  
• HDFS
  
• Experience with
  software engineering tools:
  
• JIRA
  
• Jenkins
  
• Git
  
• Confluence
  
• Strong foundation in
  algorithms and data structures