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Computer Vision Scientist - Machine Learning
Computer Vision Scientist - Machine Learning
FarmGuide's logo

Computer Vision Scientist - Machine Learning

Anupam Arya's profile picture
Posted by Anupam Arya
0 - 8 yrs
₹7L - ₹14L / yr
Delhi, Gurugram, Noida
Skills
Computer Security
Image processing
OpenCV
skill iconPython
Rational ClearCase
SAS GIS
AWS Simple Notification Service (SNS)
Startup
Cloudera
skill iconMachine Learning (ML)
Game Design
skill iconData Science
skill iconAmazon Web Services (AWS)
FarmGuide is a data driven tech startup aiming towards digitizing the periodic processes in place and bringing information symmetry in agriculture supply chain through transparent, dynamic & interactive software solutions. We, at FarmGuide (https://angel.co/farmguide) help Government in relevant and efficient policy making by ensuring seamless flow of information between stakeholders.Job Description :We are looking for individuals who want to help us design cutting edge scalable products to meet our rapidly growing business. We are building out the data science team and looking to hire across levels.- Solving complex problems in the agri-tech sector, which are long-standing open problems at the national level.- Applying computer vision techniques to satellite imagery to deduce artefacts of interest.- Applying various machine learning techniques to digitize existing physical corpus of knowledge in the sector.Key Responsibilities :- Develop computer vision algorithms for production use on satellite and aerial imagery- Implement models and data pipelines to analyse terabytes of data.- Deploy built models in production environment.- Develop tools to assess algorithm accuracy- Implement algorithms at scale in the commercial cloudSkills Required :- B.Tech/ M.Tech in CS or other related fields such as EE or MCA from IIT/NIT/BITS but not compulsory. - Demonstrable interest in Machine Learning and Computer Vision, such as coursework, open-source contribution, etc.- Experience with digital image processing techniques - Familiarity/Experience with geospatial, planetary, or astronomical datasets is valuable- Experience in writing algorithms to manipulate geospatial data- Hands-on knowledge of GDAL or open-source GIS tools is a plus- Familiarity with cloud systems (AWS/Google Cloud) and cloud infrastructure is a plus- Experience with high performance or large scale computing infrastructure might be helpful- Coding ability in R or Python. - Self-directed team player who thrives in a continually changing environmentWhat is on offer :- High impact role in a young start up with colleagues from IITs and other Tier 1 colleges- Chance to work on the cutting edge of ML (yes, we do train Neural Nets on GPUs) - Lots of freedom in terms of the work you do and how you do it - Flexible timings - Best start-up salary in industry with additional tax benefits
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Subodh Popalwar's profile image

Subodh Popalwar

Software Engineer, Memorres
For 2 years, I had trouble finding a company with good work culture and a role that will help me grow in my career. Soon after I started using Cutshort, I had access to information about the work culture, compensation and what each company was clearly offering.
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About FarmGuide

Founded :
2014
Type :
Products & Services
Size :
100-1000
Stage :
Raised funding
About
Farmguide is building a tech enabled tool to build farmer's database collected through field agents and stored in the cloud. This can later be processed to meet the needs of various stakeholders such as banks, input providers, agro commodity players, procurement managers, logistic agro supply chain. The platform also enables farmers to plan crops, take precautionary decisions about weather, pest attacks and connect to markets. Currently in stealth mode
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Subodh Popalwar's profile image

Subodh Popalwar

Software Engineer, Memorres
For 2 years, I had trouble finding a company with good work culture and a role that will help me grow in my career. Soon after I started using Cutshort, I had access to information about the work culture, compensation and what each company was clearly offering.
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