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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
Skills:
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
About Sizzle
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.
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• Charting learning journeys with knowledge graphs.
• Predicting memory decay based upon an advanced cognitive model.
• Ensure content quality via study behavior anomaly detection.
• Recommend tags using NLP for complex knowledge.
• Auto-associate concept maps from loosely structured data.
• Predict knowledge mastery.
• Search query personalization.
Requirements:
• 6+ years experience in AI/ML with end-to-end implementation.
• Excellent communication and interpersonal skills.
• Expertise in SageMaker, TensorFlow, MXNet, or equivalent.
• Expertise with databases (e. g. NoSQL, Graph).
• Expertise with backend engineering (e. g. AWS Lambda, Node.js ).
• Passionate about solving problems in education
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As a machine learning engineer on the team, you will
• Help science and product teams innovate in developing and improving end-to-end
solutions to machine learning-based security/privacy control
• Partner with scientists to brainstorm and create new ways to collect/curate data
• Design and build infrastructure critical to solving problems in privacy-preserving machine
learning
• Help team self-organize and follow machine learning best practice.
Basic Qualifications
• 4+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• 4+ years of programming experience with at least one modern language such as Java,
C++, or C# including object-oriented design
• 4+ years of professional software development experience
• 4+ years of experience as a mentor, tech lead OR leading an engineering team
• 4+ years of professional software development experience in Big Data and Machine
Learning Fields
• Knowledge of common ML frameworks such as Tensorflow, PyTorch
• Experience with cloud provider Machine Learning tools such as AWS SageMaker
• Programming experience with at least two modern language such as Python, Java, C++,
or C# including object-oriented design
• 3+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• Experience in python
• BS in Computer Science or equivalent
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Company Name: Curl Tech
Location: Bangalore
Website: www.curl.tech
Company Profile: Curl Tech is a deep-tech firm, based out of Bengaluru, India. Curl works on developing Products & Solutions leveraging emerging technologies such as Machine Learning, Blockchain (DLT) & IoT. We work on domains such as Commodity Trading, Banking & Financial Services, Healthcare, Logistics & Retail.
Curl has been founded by technology enthusiasts with rich industry experience. Products and solutions that have been developed at Curl, have gone on to have considerable success and have in turn become separate companies (focused on that product / solution).
If you are looking for a job, that would challenge you and desire to work with an organization that disrupts entire value chain; Curl is the right one for you!
Designation: Data Scientist or Junior Data Scientist (according to experience)
Job Description:
Good with Machine Learning and Deep learning, good with programming and maths.
Details: The candidate will be working on many image analytics/ numerical data analytics projects. The work involves, data collection, building the machine learning models, deployment, client interaction and publishing academic papers.
Responsibilities:
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The candidate will be working on many image analytics/numerical data projects.
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Candidate will be building various machine learning models depending upon the requirements.
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Candidate would be responsible for deployment of the machine learning models.
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Candidate would be the face of the company in front of the clients and will have regular client interactions to understand that client requirements.
What we are looking for candidates with:
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Basic Understanding of Statistics, Time Series, Machine Learning, Deep Learning, and their fundamentals and mathematical underpinnings.
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Proven code proficiency in Python,C/C++ or any other AI language of choice.
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Strong algorithmic thinking, creative problem solving and the ability to take ownership and do independent
research.
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Understanding how things work internally in ML and DL models is a must.
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Understanding of the fundamentals of Computer Vision and Image Processing techniques would be a plus.
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Expertise in OpenCV, ML/Neural networks technologies and frameworks such as PyTorch, Tensorflow would be a
plus.
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Educational background in any quantitative field (Computer Science / Mathematics / Computational Sciences and related disciplines) will be given preference.
Education: BE/ BTech/ B.Sc.(Physics or Mathematics)/Masters in Mathematics, Physics or related branches.
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THE IDEAL CANDIDATE WILL
- Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
- Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
- Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
- Work hands-on across various MLOps problems and provide thought leadership
- Grow and manage large teams with diverse skillsets
- Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists
ELIGIBILITY CRITERIA
- BE/BTech/MTech (Specialization/courses in ML/DS)
- At-least 7+ years of Consulting services delivery experience
- Very strong problem-solving skills & work ethics
- Possesses strong analytical/logical thinking, storyboarding and executive communication skills
- 5+ years of experience in Python/R, SQL
- 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
- Hands on work experience in DevOps
- Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
- Exposure on cloud technologies like Azure, AWS or GCP
- Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
- Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
- Experience with one or more Container-ecosystem (Docker, Kubernetes)
- Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
- Good understanding of OOP & Data Structures concepts
Nice to Have:
- Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
- Experience in Helm is a plus
- Strong understanding of data infrastructure, data warehouse, or data engineering
You can expect to –
- Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
- Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
- Work in a diverse environment that keeps evolving
- Hone your entrepreneurial skills as you contribute to growth of the organization
2-5 yrs of proven experience in ML, DL, and preferably NLP.
Preferred Educational Background - B.E/B.Tech, M.S./M.Tech, Ph.D.
𝐖𝐡𝐚𝐭 𝐰𝐢𝐥𝐥 𝐲𝐨𝐮 𝐰𝐨𝐫𝐤 𝐨𝐧?
𝟏) Problem formulation and solution designing of ML/NLP applications across complex well-defined as well as open-ended healthcare problems.
2) Cutting-edge machine learning, data mining, and statistical techniques to analyse and utilise large-scale structured and unstructured clinical data.
3) End-to-end development of company proprietary AI engines - data collection, cleaning, data modelling, model training / testing, monitoring, and deployment.
4) Research and innovate novel ML algorithms and their applications suited to the problem at hand.
𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐰𝐞 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐟𝐨𝐫?
𝟏) Deeper understanding of business objectives and ability to formulate the problem as a Data Science problem.
𝟐) Solid expertise in knowledge graphs, graph neural nets, clustering, classification.
𝟑) Strong understanding of data normalization techniques, SVM, Random forest, data visualization techniques.
𝟒) Expertise in RNN, LSTM, and other neural network architectures.
𝟓) DL frameworks: Tensorflow, Pytorch, Keras
𝟔) High proficiency with standard database skills (e.g., SQL, MongoDB, Graph DB), data preparation, cleaning, and wrangling/munging.
𝟕) Comfortable with web scraping, extracting, manipulating, and analyzing complex, high-volume, high-dimensionality data from varying sources.
𝟖) Experience with deploying ML models on cloud platforms like AWS or Azure.
9) Familiarity with version control with GIT, BitBucket, SVN, or similar.
𝐖𝐡𝐲 𝐜𝐡𝐨𝐨𝐬𝐞 𝐮𝐬?
𝟏) We offer Competitive remuneration.
𝟐) We give opportunities to work on exciting and cutting-edge machine learning problems so you contribute towards transforming the healthcare industry.
𝟑) We offer flexibility to choose your tools, methods, and ways to collaborate.
𝟒) We always value and believe in new ideas and encourage creative thinking.
𝟓) We offer open culture where you will work closely with the founding team and have the chance to influence the product design and execution.
𝟔) And, of course, the thrill of being part of an early-stage startup, launching a product, and seeing it in the hands of the users.
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Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.
What will you do?
- You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
- You will be constantly assessing and improving the model using techniques like Transfer learning
- You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
- You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
- Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
- Building predictive models and machine-learning algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Presenting information using data visualization techniques and proposing solutions and strategies to business challenges
We would love to hear from you if :
- You have 2+ years of experience as a software engineer at a SaaS or technology company
- Demonstrable hands-on programming experience with Python/R Data Science Stack
- Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
- Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
- Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
- Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
- Preferable Experience Experienced in web crawling and data scraping
- Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
- Experience with text mining, pattern matching and fuzzy matching
Why Tartan?
- Brand new Macbook
- Stock Options
- Health Insurance
- Unlimited Sick Leaves
- Passion Fund (Invest in yourself or your passion project)
- Wind Down
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- Perform research and development on Machine Learning specifically in the areas of Speech Recognition, Digital signal processing, audio signal processing, NaturalLanguage processing, Natural Language Understanding
- Read and keep up with the research in Speech recognition, Machine Learning, Deep
- Understand and implement research papers to the business problem and build the
- Contribute to applied research and open source community
- Mentor and guide team members
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