Computer Vision Scientist (Geospatial Analysis)
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Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Designation Computer Vision Scientist (Geospatial Analysis)
Location - Bangalore
Position - Full-Time (No Hybrid)
Salary Competitive
Company QueNext
About Us
AI ML Startup set up in 2015 which is in the domain of power banking agriculture sector etc. and working directly with Karnataka Govt to offer insights and decisions.
Company website: -
About Us
AI ML Startup set up in 2015 which is in the domain of power banking agriculture sector etc. and working directly with Karnataka Govt to offer insights and decisions.
You will be part of the team that is delivering large transformational projects to
energy utilities banks and government bodies utilizing our in-house patented AI
driven products.
You will be working on cutting edge geospatial technologies with a steep learning
curve and working along-side the founders from Indian Statistical Institute (ISI) and
INSEAD and a team of data scientists and programmers in a collaborative and
innovative environment.
You should have a strong understanding and interest in remote sensing and coding.
A superior academic record at a leading university in Computer Science Data
Science and Technology Geoinformatics Mathematics Statistics or a related field
or equivalent work experience is preferable.
Please send in your applications to Aren at If possible Please
include links to projects developed by you.
Job Description:
We are seeking a highly skilled and innovative Computer Vision Scientist to join us
team.
The ideal candidate will have expertise in geographic information systems (GIS)
hands-on experience with Apache Kafka TensorFlow and machine learning (ML)
pipelines and a strong background in computer vision.
You will bring your familiarity and experience with satellite and aerial imagery
geospatial APIs and libraries knowledge of containerization and orchestration tools
(e.g. Docker Kubernetes) and Understanding of Big Data frameworks (e.g. Spark
Hadoop) in geospatial contexts.
This role is ideal for someone passionate about developing advanced geospatial
applications integrating cutting-edge technologies and solving complex spatial data
challenges.
Key Responsibilities:
GIS Development:
Design develop and implement GIS-based applications and services.
Create manipulate and analyze geospatial data
Integrate geospatial data into larger software systems
Machine Learning Pipelines:
Build optimize and deploy ML pipelines for geospatial and computer
vision tasks
Leverage TensorFlow to create models for spatial analysis object
detection and image classification
Implement ML workflows from data ingestion to deployment and
monitoring
Kafka Integration:
Develop real-time data streaming and processing workflows using
Apache Kafka
Design event-driven systems for geospatial and computer vision
applications
Ensure scalability reliability and efficiency in Kafka-based pipelines
Computer Vision Applications:
Apply computer vision techniques to geospatial data satellite imagery
and aerial photography
Develop and deploy models for tasks like feature extraction land-use
classification and object recognition
Stay updated on advancements in CV to enhance project outcomes
Collaboration and Documentation:
Collaborate with cross-functional teams including data scientists
software engineers and GIS analysts
Document workflows processes and technical details for easy
replication and scalability
Provide technical support and troubleshooting for GIS and ML-related
challenges
Technical Skills:
Proficiency in GIS tools
Strong expertise in Apache Kafka for real-time data streaming.
Experience with TensorFlow Keras or PyTorch for ML model development
Knowledge of machine learning pipelines and tools (e.g. Kubeflow Airflow).
Hands-on experience with computer vision techniques and libraries (e.g.
OpenCV TensorFlow Object Detection API).
Strong programming skills in Python Java or C.
Familiarity with cloud platforms (e.g. AWS Azure GCP) for ML and GIS
deployment.
Knowledge of geospatial data formats (e.g. GeoJSON Shapefiles Raster).
Location - Bangalore
Position - Full-Time (No Hybrid)
Salary Competitive
Company QueNext
About Us
AI ML Startup set up in 2015 which is in the domain of power banking agriculture sector etc. and working directly with Karnataka Govt to offer insights and decisions.
Company website: -
About Us
AI ML Startup set up in 2015 which is in the domain of power banking agriculture sector etc. and working directly with Karnataka Govt to offer insights and decisions.
You will be part of the team that is delivering large transformational projects to
energy utilities banks and government bodies utilizing our in-house patented AI
driven products.
You will be working on cutting edge geospatial technologies with a steep learning
curve and working along-side the founders from Indian Statistical Institute (ISI) and
INSEAD and a team of data scientists and programmers in a collaborative and
innovative environment.
You should have a strong understanding and interest in remote sensing and coding.
A superior academic record at a leading university in Computer Science Data
Science and Technology Geoinformatics Mathematics Statistics or a related field
or equivalent work experience is preferable.
Please send in your applications to Aren at If possible Please
include links to projects developed by you.
Job Description:
We are seeking a highly skilled and innovative Computer Vision Scientist to join us
team.
The ideal candidate will have expertise in geographic information systems (GIS)
hands-on experience with Apache Kafka TensorFlow and machine learning (ML)
pipelines and a strong background in computer vision.
You will bring your familiarity and experience with satellite and aerial imagery
geospatial APIs and libraries knowledge of containerization and orchestration tools
(e.g. Docker Kubernetes) and Understanding of Big Data frameworks (e.g. Spark
Hadoop) in geospatial contexts.
This role is ideal for someone passionate about developing advanced geospatial
applications integrating cutting-edge technologies and solving complex spatial data
challenges.
Key Responsibilities:
GIS Development:
Design develop and implement GIS-based applications and services.
Create manipulate and analyze geospatial data
Integrate geospatial data into larger software systems
Machine Learning Pipelines:
Build optimize and deploy ML pipelines for geospatial and computer
vision tasks
Leverage TensorFlow to create models for spatial analysis object
detection and image classification
Implement ML workflows from data ingestion to deployment and
monitoring
Kafka Integration:
Develop real-time data streaming and processing workflows using
Apache Kafka
Design event-driven systems for geospatial and computer vision
applications
Ensure scalability reliability and efficiency in Kafka-based pipelines
Computer Vision Applications:
Apply computer vision techniques to geospatial data satellite imagery
and aerial photography
Develop and deploy models for tasks like feature extraction land-use
classification and object recognition
Stay updated on advancements in CV to enhance project outcomes
Collaboration and Documentation:
Collaborate with cross-functional teams including data scientists
software engineers and GIS analysts
Document workflows processes and technical details for easy
replication and scalability
Provide technical support and troubleshooting for GIS and ML-related
challenges
Technical Skills:
Proficiency in GIS tools
Strong expertise in Apache Kafka for real-time data streaming.
Experience with TensorFlow Keras or PyTorch for ML model development
Knowledge of machine learning pipelines and tools (e.g. Kubeflow Airflow).
Hands-on experience with computer vision techniques and libraries (e.g.
OpenCV TensorFlow Object Detection API).
Strong programming skills in Python Java or C.
Familiarity with cloud platforms (e.g. AWS Azure GCP) for ML and GIS
deployment.
Knowledge of geospatial data formats (e.g. GeoJSON Shapefiles Raster).
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
