11+ Speech recognition Jobs in Mumbai | Speech recognition Job openings in Mumbai
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Solve problems in speech and NLP domain using advanced Deep learning and Machine Learning techniques. Few examples of the problems are -
* Limited resource Speaker Diarization on mono-channel recordings in noisy environment.
* Speech Enhancement to improve accuracy of downstream speech analytics tasks.
* Automated Speech Recognition for accent heavy audio with a noisy background.
* Speech analytic tasks, which include: emotions, empathy, keyword extraction.
* Text analytic tasks, which include: topic modeling, entity and intent extraction, opinion mining, text classification, and sentiment detection on multilingual data.
A typical day at work
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You will work closely with the product team to own a business problem. You will then model the business problem into a Machine Learning problem. Next you will do literature review to identify approaches to solve the problem. Test these approaches, identify the best approach, add your own insights to improve the performance and ship that to production!
What should you know?
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* Solid understanding of Classical Machine Learning and Deep Learning concepts and algorithms.
* Experience with literature review either in academia or industry.
* Proficiency in at least one programming language such as Python, C, C++, Java, etc.
* Proficiency in Machine Learning tools such as TensorFlow, Keras, Caffe, Torch/PyTorch or Theano.
* Advanced degree in Computer Science, Electrical Engineering, Machine Learning, Mathematics, Statistics, Physics, or Computational Linguistics
Why DeepAffects?
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* You’ll learn insanely fast here.
* Esops and competitive compensation.
* Opportunity and encouragement for publishing research at top conferences, paid trips to attend workshop and conferences where you have published.
* Independent work, flexible timings and sense of ownership of your work.
* Mentorship from distinguished researchers and professors.
Team:- We are a team of 9 data scientists working on Video Analytics Projects, Data Analytics projects for internal AI requirements of Reliance Industries as well for the external business. At a time, we make progress on multiple projects(atleast 4) in Video Analytics or Data Analytics.
Responsibilities
- Work on execution and scheduling of all tasks related to assigned projects' deliverable dates
- Optimize and debug existing codes to make them scalable and improve performance
- Design, development, and delivery of tested code and machine learning models into production environments
- Work effectively in teams, managing and leading teams
- Provide effective, constructive feedback to the delivery leader
- Manage client expectations and work with an agile mindset with machine learning and AI technology
- Design and prototype data-driven solutions
Eligibility
- Highly experienced in designing, building, and shipping scalable and production-quality machine learning algorithms in the field of Python applications
- Working knowledge and experience in NLP core components (NER, Entity Disambiguation, etc.)
- In-depth expertise in Data Munging and Storage (Experienced in SQL, NoSQL, MongoDB, Graph Databases)
- Expertise in writing scalable APIs for machine learning models
- Experience with maintaining code logs, task schedulers, and security
- Working knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
- Experience with at least one of the following: Keras, Tensorflow, Caffe, or PyTorch
Role: Principal Software Engineer
We looking for a passionate Principle Engineer - Analytics to build data products that extract valuable business insights for efficiency and customer experience. This role will require managing, processing and analyzing large amounts of raw information and in scalable databases. This will also involve developing unique data structures and writing algorithms for the entirely new set of products. The candidate will be required to have critical thinking and problem-solving skills. The candidates must be experienced with software development with advanced algorithms and must be able to handle large volume of data. Exposure with statistics and machine learning algorithms is a big plus. The candidate should have some exposure to cloud environment, continuous integration and agile scrum processes.
Responsibilities:
• Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule
• Software Development that creates data driven intelligence in the products which deals with Big Data backends
• Exploratory analysis of the data to be able to come up with efficient data structures and algorithms for given requirements
• The system may or may not involve machine learning models and pipelines but will require advanced algorithm development
• Managing, data in large scale data stores (such as NoSQL DBs, time series DBs, Geospatial DBs etc.)
• Creating metrics and evaluation of algorithm for better accuracy and recall
• Ensuring efficient access and usage of data through the means of indexing, clustering etc.
• Collaborate with engineering and product development teams.
Requirements:
• Master’s or Bachelor’s degree in Engineering in one of these domains - Computer Science, Information Technology, Information Systems, or related field from top-tier school
• OR Master’s degree or higher in Statistics, Mathematics, with hands on background in software development.
• Experience of 8 to 10 year with product development, having done algorithmic work
• 5+ years of experience working with large data sets or do large scale quantitative analysis
• Understanding of SaaS based products and services.
• Strong algorithmic problem-solving skills
• Able to mentor and manage team and take responsibilities of team deadline.
Skill set required:
• In depth Knowledge Python programming languages
• Understanding of software architecture and software design
• Must have fully managed a project with a team
• Having worked with Agile project management practices
• Experience with data processing analytics and visualization tools in Python (such as pandas, matplotlib, Scipy, etc.)
• Strong understanding of SQL and querying to NoSQL database (eg. Mongo, Casandra, Redis
Who Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- 4+ years of industrial experience in computer vision and/or deep learning
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
Who Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- 4+ years of industrial experience in computer vision and/or deep learning
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
We are looking for an engineer with ML/DL background.
Ideal candidate should have the following skillset
1) Python
2) Tensorflow
3) Experience building and deploying systems
4) Experience with Theano/Torch/Caffe/Keras all useful
5) Experience Data warehousing/storage/management would be a plus
6) Experience writing production software would be a plus
7) Ideal candidate should have developed their own DL architechtures apart from using open source architechtures.
8) Ideal candidate would have extensive experience with computer vision applications
Candidates would be responsible for building Deep Learning models to solve specific problems. Workflow would look as follows:
1) Define Problem Statement (input -> output)
2) Preprocess Data
3) Build DL model
4) Test on different datasets using Transfer Learning
5) Parameter Tuning
6) Deployment to production
Candidate should have experience working on Deep Learning with an engineering degree from a top tier institute (preferably IIT/BITS or equivalent)
We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations , clinical named entity recognition and information extraction from clinical notes.
This is a role for highly technical machine learning & data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.
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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Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap
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Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs
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Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists
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Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space
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Partner with the executive team and other business leaders to deliver cross-functional research work and models
Required Skills:
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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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Knowledge of deep learning & NLP
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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.
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Experience with GPU computing is a plus.
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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.
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Expert-level experience with a wide range of quantitative methods that can be applied to business problems.
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Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization.
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Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.
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Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling
Qualifications
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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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Expert-level experience with machine learning that can be applied to business problems
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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
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Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling
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Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application)
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5+ years of industry experience in data science and machine learning, preferably at a software product company
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3+ years of experience managing data science teams, incl. managing/grooming managers beneath you
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3+ years of experience partnering with executive staff on data topics
2. Should understand the importance and know-how of taking the machine-learning-based solution to the consumer.
3. Hands-on experience with statistical, machine-learning tools and techniques
4. Good exposure to Deep learning libraries like Tensorflow, PyTorch.
5. Experience in implementing Deep Learning techniques, Computer Vision and NLP. The candidate should be able to develop the solution from scratch with Github codes exposed.
6. Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library.
7. Should be strong in data structures and algorithms. Should be able to do code complexity analysis/optimization for smooth delivery to production.
8. Expert level coding experience in Python.
9. Technologies: Backend - Python (Programming Language)
10. Should have the ability to think long term solutions, modularity, and reusability of the components.
11. Should be able to work in a collaborative way. Should be open to learning from peers as well as constantly bring new ideas to the table.
12. Self-driven missile. Open to peer criticism, feedback and should be able to take it positively. Ready to be held accountable for the responsibilities undertaken.