05 Aug
|
Recognized
|
Chennai
05 Aug
Recognized
Chennai
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.
The role requires close collaboration with ISP, camera, embedded, data analytics, and product teams to translate real -world imaging challenges into scalable AI -powered vision solutions.
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
- Solid 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