Lightning Job By Cutshort ⚡
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With over 20 years of expertise in broadcasting, postproduction and IT infrastructure, we have implemented large-scale, multi-platform convergence projects. Desynova is a unique company formed by a unique mix of skill sets and experience which makes us stand out in the industry. We are a team of founders and leaders in diverse fields of the technology landscape, where many players from the video and IP worlds are still learning the basic terrain. And for a few who do know the technology, proposing a suitable and profitable solution to the client, is still a challenge. Digital technologies are revolutionizing not just backend efficiency and productivity, but frontend consumer user interfaces and services in entertainment and beyond. Most players, however, do not have the expertise to fully take advantage of these technologies and very few service providers exist with complete lifecycle experience in designing and implementing cutting-edge solutions. Desynova enables its customers to reach any screen, at any time, with any content from any location in the world and to maximize return on their valuable video assets.
Below are the responsibilities and requirements for the Data Science role:-
• AI-ML background with exp>4 yrs.
• Experience in deep learning, machine learning, OpenCV, NLP, Generative AI, and cloud deployment.
• Hands-on Python coding experience between 4-5 years.
• Should be able to fetch codes from Git Hub and modify them as per the in-house requirements.
• Should Have worked on audio, image, video, and textual datasets.
• Should have exposure to Nvidia Servers.
• Knowledge of GitHub commits and version maintenance.
• Awareness of the latest technologies like Chat GPT, openAI, Whisper, etc.
• Exposure to Azure, AWS EC2, Docker, and Container. Minimum 3 years exp req.
• Research and implement appropriate ML algorithms and tools.
• Perform statistical analysis and fine-tuning using test results.
• Train and retrain systems when necessary.
• Extend existing ML libraries and frameworks.
• Familiarity with machine learning frameworks (like Keras or PyTorch, TensorFlow)
• Understanding of data structures, data modeling, and software architecture.
• Deep knowledge of math, probability, statistics, and algorithms.
Subodh PopalwarSoftware Engineer, Memorres
We’re a new-age internet company that is all about solving problems and cutting the cords of the M&E industry. Established in 2017, we at Desynova envision a future for media production that relies on sharp and convenient technology, eliminating manual reliance, simplifying the workflow and automating operations through a single cloud-native platform.
Since our genesis, we have done some mind-boggling stuff for the major players of the broadcasting industry; specifically the largest broadcasting network in Asia and the biggest OTT platform in the world. Contido, our content supply chain management platform, has been doing just that; decluttering and recalibrating the canvas of media production.
Our USP is not solely our product, but our insatiable need to better what is good and sell only what’s best. We’re only getting started. Join us to put yourself on the map, as we venture into global terrains.
We're here to re-imagine a media production workspace without the usual theatre of scores of humans, cluttered spaces, unorganized communication and so much more.
Sizzle is an exciting new startup that’s changing the world of gaming. At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams. We’re looking for a superstar engineer that is well versed with AI and audio technologies around audio detection, speech-to-text, interpretation, and sentiment analysis.
You will be responsible for:
Developing audio algorithms to detect key moments within popular online games, such as:
Streamer speaking, shouting, etc.
Gunfire, explosions, and other in-game audio events
Speech-to-text and sentiment analysis of the streamer’s narration
Leveraging baseline technologies such as TensorFlow and others -- and building models on top of them
Building neural network architectures for audio analysis as it pertains to popular games
Specifying exact requirements for training data sets, and working with analysts to create the data sets
Training final models, including techniques such as transfer learning, data augmentation, etc. to optimize models for use in a production environment
Working with back-end engineers to get all of the detection algorithms into production, to automate the highlight creation
You should have the following qualities:
Solid understanding of AI frameworks and algorithms, especially pertaining to audio analysis, speech-to-text, sentiment analysis, and natural language processing
Experience using Python, TensorFlow and other AI tools
Demonstrated understanding of various algorithms for audio analysis, such as CNNs, LSTM for natural language processing, and others
Nice to have: some familiarity with AI-based audio analysis including sentiment analysis
Familiarity with AWS environments
Excited about working in a fast-changing startup environment
Willingness to learn rapidly on the job, try different things, and deliver results
Ideally a gamer or someone interested in watching gaming content online
Machine Learning, Audio Analysis, Sentiment Analysis, Speech-To-Text, Natural Language Processing, Neural Networks, TensorFlow, OpenCV, AWS, Python
Work Experience: 2 years to 10 years
Sizzle is building AI to automate gaming highlights, directly from Twitch and YouTube videos. Presently, there are over 700 million fans around the world that watch gaming videos on Twitch and YouTube. Sizzle is creating a new highlights experience for these fans, so they can catch up on their favorite streamers and esports leagues. Sizzle is available at http://www.sizzle.gg">www.sizzle.gg.
● B.Tech/Masters in Mathematics, Statistics, Computer Science or another quantitative field
● 2-3+ years of work experience in ML domain ( 2-5 years experience )
● Hands-on coding experience in Python
● Experience in machine learning techniques such as Regression, Classification,Predictive modeling, Clustering, Deep Learning stack, NLP.
● Working knowledge of Tensorflow/PyTorch
● Experience with distributed computing frameworks: Map/Reduce, Hadoop, Spark etc.
● Experience with databases: MongoDB
Researches, develops and maintains machine learning and statistical models for
Work across the spectrum of statistical modelling including supervised,
unsupervised, & deep learning techniques to apply the right level of solution to
the right problem Coordinate with different functional teams to monitor outcomes and refine/
improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation
Identify unexplored data opportunities for the business to unlock and maximize
the potential of digital data within the organization
Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data
3+ years of experience solving complex business problems using machine
Fluency in programming languages such as Python, NLP and Bert, is a must
Strong analytical and critical thinking skills
Experience in building production quality models using state-of-the-art technologies
Familiarity with databases .
desirable Ability to collaborate on projects and work independently when required.
Previous experience in Fintech/payments domain is a bonus
You should have Bachelor’s or Master’s degree in Computer Science, Statistics
or Mathematics or another quantitative field from a top tier Institute
Machine Learning & Deep Learning – Strong
Experienced in TensorFlow, PyTorch, ONNX, Object Detection, Pretrained Models like YOLO, SSD, Faster RCNN, etc…
Python – Strong
NumPy, Pandas, OpenCV
Problem Solving - strong
C++ - average
It will be good if candidate have working experience in C++ in any domain
Note :: Looking for Immediate to 30 days of Notice Period
- Design and develop strong analytics system and predictive models
- Managing a team of data scientists, machine learning engineers, and big data specialists
- Identify valuable data sources and automate data collection processes
- Undertake pre-processing of structured and unstructured data
- Analyze large amounts of information to discover trends and patterns
- Build predictive models and machine-learning algorithms
- Combine models through ensemble modeling
- Present information using data visualization techniques
- Propose solutions and strategies to business challenges
- Collaborate with engineering and product development teams
- Proven experience as a seasoned Data Scientist
- Good Experience in data mining processes
- Understanding of machine learning and Knowledge of operations research is a value addition
- Strong understanding and experience in R, SQL, and Python; Knowledge base with Scala, Java, or C++ is an asset
- Experience using business intelligence tools (e. g. Tableau) and data frameworks (e. g. Hadoop)
- Strong math skills (e. g. statistics, algebra)
- Problem-solving aptitude
- Excellent communication and presentation skills
- Experience in Natural Language Processing (NLP)
- Strong competitive coding skills
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
Proactively fetches information from various sources and analyzes it for a better understanding of how the business performs, and to build AI tools that automate certain processes within the company.
Roles & Responsibilities
- Develop novel computer vision/NLP algorithms
- Build large datasets that will be used to train the models
- Empirically evaluate related research works
- Train and evaluate deep learning architectures on multiple large scale datasets
- Collaborate with the rest of the research team to produce high quality research
- Manage a team of 2+ interns
- 2+years of experience in building deep learning models
- Strong basics around probability and statistics, linear algebra, data structure & algorithms
- Good knowledge of classic ML algorithms (regression, SVM, PCA etc.), deep learning
- Strong programming skills
Nice to have skills
- Familiarity with pytorch
- Knowledge of SOTA techniques in NLP and Vision
- High level of responsibility and ownership for a product impacting billions of lives.
- Extremely high-quality talent to work with. Work with a global team between US / India.
- Work from anywhere anytime!
- Best of breed industry benefits packages.
About us: Nexopay helps transforming digital payments and enabling instant financing for parents, across schools and colleges world-wide.
- Work with stakeholders throughout the organisation and across entities to identify opportunities for leveraging internal and external data to drive business impact
- Mine and analyze data to improve and optimise performance, capture meaningful insights and turn them into business advantages
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Develop custom data models and algorithms to apply to data sets
- Use predictive modeling to predict outcomes and identify key drivers
- Coordinate with different functional teams to implement models and monitor outcomes
- Develop processes and tools to monitor and analyze model performance and data accuracy
- Experience in solving business problem using descriptive analytics, statistical modelling / machine learning
- 2+ years of strong working knowledge of SQL language
- Experience with visualization tools e. g., Tableau, Power BI
- Working knowledge on handling analytical projects end to end using industry standard tools (e. g., R, Python)
- Strong presentation and communication skills
- Experience in education sector is a plus
- Fluency in English
Turing enables U.S. companies to hire the world’s best remote software engineers. 100+ companies including those backed by Sequoia, Andreessen, Google Ventures, Benchmark, Founders Fund, Kleiner, Lightspeed, and Bessemer have hired Turing engineers. For more than 180,000 engineers across 140 countries, we are the preferred platform for finding remote U.S. software engineering roles. We offer a wide range of full-time remote opportunities for full-stack, backend, frontend, DevOps, mobile, and AI/ML engineers.
We are growing fast (our revenue 15x’d in the past 12 months and is accelerating), and we have raised $14M in seed funding (https://tcrn.ch/3lNKbM9">one of the largest in Silicon Valley) from:
- Facebook’s 1st CTO and Quora’s Co-Founder (Adam D’Angelo)
- Executives from Google, Facebook, Square, Amazon, and Twitter
- Foundation Capital (investors in Uber, Netflix, Chegg, Lending Club, etc.)
- Cyan Banister
- Founder of Upwork (Beerud Sheth)
We also raised a much larger round of funding in October 2020 that we will be publicly announcing over the coming month.
Some articles about Turing:
- https://techcrunch.com/2020/08/25/turing-raises-14m-to-help-source-vet-place-and-manage-remote-developers-in-tech-jobs/">TechCrunch: Turing raises $14M seed to help source, vet, place, and manage remote developers
- https://www.theinformation.com/articles/six-startups-prospering-during-coronavirus">The Information: Six Startups Prospering During Coronavirus
- https://medium.com/@cyanbanister/turing-helps-the-world-level-up-ff44b4e6415d">Cyan Banister: Turing Helps the World Level Up
- https://turing.com/boundarylessblog/2019/10/the-future-of-work-is-remote/the-future-of-work/">Jonathan Siddharth (Turing CEO): The Future of Work is Remote.
Turing is led by successful repeat founders Jonathan Siddharth and Vijay Krishnan, whose last A.I. company leveraged elite remote talent and had a successful acquisition. (https://techcrunch.com/2017/02/23/revcontent-acquires-rover/">Techcrunch story). Turing’s leadership team is composed of ex-Engineering and Sales leadership from Facebook, Google, Uber, and Capgemini.
About the role:
Software developers from all over the world have taken 200,000+ tests and interviews on Turing. Turing has also recommended thousands of developers to its customers and got customer feedback in terms of customer interview pass/fail data and data from the success of the collaboration with a U.S customer. This generates a massive proprietary dataset with a rich feature set comprising resume and test/interview features and labels in the form of actual customer feedback. Continuing rapid growth in our business creates an ever-increasing data advantage for us.
We are looking for a Machine Learning Scientist who can help solve a whole range of exciting and valuable machine learning problems at Turing. Turing collects a lot of valuable heterogeneous signals about software developers including their resume, GitHub profile and associated code and a lot of fine-grained signals from Turing’s own screening tests and interviews (that span various areas including Computer Science fundamentals, project ownership and collaboration, communication skills, proactivity and tech stack skills), their history of successful collaboration with different companies on Turing, etc.
A machine learning scientist at Turing will help create deep developer profiles that are a good representation of a developer’s strengths and weaknesses as it relates to their probability of getting successfully matched to one of Turing’s partner companies and having a fruitful long-term collaboration. The ML scientist will build models that are able to rank developers for different jobs based on their probability of success at the job.
You will also help make Turing’s tests more efficient by assessing their ability to predict the probability of a successful match of a developer with at least one company. The prior probability of a registered developer getting matched with a customer is about 1%. We want our tests to adaptively reduce perplexity as steeply as possible and move this probability estimate rapidly toward either 0% or 100%; maximize expected information-gain per unit time in other words.
As an ML Scientist on the team, you will have a unique opportunity to make an impact by advancing ML models and systems, as well as uncovering new opportunities to apply machine learning concepts to Turing product(s).
This role will directly report to Turing’s founder and CTO, https://www.linkedin.com/in/vijay0/">Vijay Krishnan. This is his https://scholar.google.com/citations?user=uCRc7DgAAAAJ&hl=en">Google Scholar profile.
- Enhance our existing machine learning systems using your core coding skills and ML knowledge.
- Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems.
- Utilize state-of-the-art ML modeling techniques to predict user interactions and the direct impact on the company’s top-line metrics.
- Design features and builds large scale recommendation systems to improve targeting and engagement.
- Identify new opportunities to apply machine learning to different parts of our product(s) to drive value for our customers.
- BS, MS, or Ph.D. in Computer Science or a relevant technical field (AI/ML preferred).
- Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams
- Expertise in machine learning fundamentals, applicable to search - Learning to Rank, Deep Learning, Tree-Based Models, Recommendation Systems, Relevance and Data mining, understanding of NLP approaches like W2V or Bert.
- 2+ years of experience applying machine learning methods in settings like recommender systems, search, user modeling, graph representation learning, natural language processing.
- Strong understanding of neural network/deep learning, feature engineering, feature selection, optimization algorithms. Proven ability to dig deep into practical problems and choose the right ML method to solve them.
- Strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
- Good understanding of mathematical foundations of machine learning algorithms.
- Ability to be available for meetings and communication during Turing's "coordination hours" (Mon - Fri: 8 am to 12 pm PST).
Other Nice-to-have Requirements:
- First author publications in ICML, ICLR, NeurIPS, KDD, SIGIR, and related conferences/journals.
- Strong performance in Kaggle competitions.
- 5+ years of industry experience or a Ph.D. with 3+ years of industry experience in applied machine learning in similar problems e.g. ranking, recommendation, ads, etc.
- Strong communication skills.
- Experienced in leading large-scale multi-engineering projects.
- Flexible, and a positive team player with outstanding interpersonal skills.
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.