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Matellio India Private Limited's logo

AI/ML Engineer

Harshit Sharma's profile picture
Posted by Harshit Sharma
3 - 6 yrs
₹3L - ₹15L / yr
Remote only
Skills
skill iconPython
skill iconMachine Learning (ML)
skill iconData Science
Natural Language Processing (NLP)
Computer Vision
skill iconDeep Learning
recommendation algorithm
This role is primarily responsible for building AIML models and cognitive applications

Principal Accountabilities :

1. Good in communication and converting business requirements to functional requirements

2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data

3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.

5. Experience in SOTA Deep Learning techniques to solve NLP problems.

6. End-to-end data collection, model development and testing, and integration into production environments.

7. Build and prototype analysis pipelines iteratively to provide insights at scale.

8. Experience in querying different data sources

9. Partner with developers and business teams for the business-oriented decisions

10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.
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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 Matellio India Private Limited

Founded :
1998
Type
Size :
100-1000
Stage :
Profitable
About

As an end-to-end web and mobile app development company, we help businesses create robust, IoT, AI/ ML, and Location-based solutions. Get in touch to book a free consultation!

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You will be responsible for setting an agenda to develop and ship machine learning models that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company, and help build a foundation of tools and practices used by quantitative staff across the company.



What you will achieve:

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  • Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience

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  • Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets.

  • Experience with GPU computing is a plus.

  • Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company.

  • Expert-level experience with a wide range of quantitative methods that can be applied to business problems.

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  • Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization

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  • Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization

  • Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

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About us
DataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.

Data Science@DataWeave
We the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.

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It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!

What do we offer?
- Some of the most challenging research problems in NLP and Computer Vision. Huge text and image datasets that you can play with!
- Ability to see the impact of your work and the value you're adding to our customers almost immediately.
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- A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible working hours.
- Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.
- Last but not the least, competitive salary packages and fast paced growth opportunities.

Who are we looking for?
The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem. You are also expected to develop capabilities that open up new business productization opportunities.


We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).


Key problem areas
- Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.
- Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.
- Document clustering, attribute tagging, data normalization, classification, summarization, sentiment analysis.
- Image based clustering and classification, segmentation, object detection, extracting text from images, generative models, recommender systems.
- Ensemble approaches for all the above problems using multiple text and image based techniques.

Relevant set of skills
- Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus, optimization, algorithms and complexity.
- Background in one or more of information retrieval, data mining, statistical techniques, natural language processing, and computer vision.
- Excellent coding skills on multiple programming languages with experience building production grade systems. Prior experience with Python is a bonus.
- Experience building and shipping machine learning models that solve real world engineering problems. Prior experience with deep learning is a bonus.
- Experience building robust clustering and classification models on unstructured data (text, images, etc). Experience working with Retail domain data is a bonus.
- Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.
- Experience working with a variety of tools and libraries for machine learning and visualization, including numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.
- Use the command line like a pro. Be proficient in Git and other essential software development tools.
- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.

Role and responsibilities
- Understand the business problems we are solving. Build data science capability that align with our product strategy.
- Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.
- Build robust clustering and classification models in an iterative manner that can be used in production.
- Constantly think scale, think automation. Measure everything. Optimize proactively.
- Take end to end ownership of the projects you are working on. Work with minimal supervision.
- Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.
- Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.
- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.
- Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.
Read more
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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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