Chief Engineer: Deep Learning Compiler Expert

• Your responsibilities:
• Build, improve and extend NLP capabilities
• Research and evaluate different approaches to NLP problems
• Must be able to write code that is well designed, produce deliverable results
• Write code that scales and can be deployed to production

You must have:

• Fundamentals of statistical methods is a must
• Experience in named entity recognition, POS Tagging, Lemmatization, vector representations of textual data and neural networks - RNN, LSTM
• A solid foundation in Python, data structures, algorithms, and general software development skills.
• Ability to apply machine learning to problems that deal with language
• Engineering ability to build robustly scalable pipelines
• Ability to work in a multi-disciplinary team with a strong product focus

About the company

 Changing the way cataloging is done across the Globe. Our vision is to empower the smallest of
sellers, situated in the farthest of corners, to create superior product images and videos, without the need
for any external professional help. Imagine 30M+ merchants shooting Product Images or Videos using
their Smartphones, and then choosing Filters for Amazon, Asos, Airbnb, Doordash, etc to instantly
compose High-Quality "tuned-in" product visuals, instantly.  
editing AI software, to capture and process beautiful product images for online selling. We are also
fortunate and proud to be backed by the biggest names in the investment community including the likes of
Accel Partners, Angellist and prominent Founders and Internet company operators, who believe that
there is an intelligent and efficient way of doing Digital Production than how the world operates currently.

Job Description :

- We are looking for a seasoned Computer Vision Engineer with AI/ML/CV and Deep Learning skills to
play a senior leadership role in our Product & Technology Research Team.
- You will be leading a team of CV researchers to build models that automatically transform millions of ecommerce, automobiles, food, real-estate ram images into processed final images.
- You will be responsible for researching the latest art of the possible in the field of computer vision,
designing the solution architecture for our offerings and lead the Computer Vision teams to build the core
algorithmic models & deploy them on Cloud Infrastructure.
- Working with the Data team to ensure your data pipelines are well set up and
models are being constantly trained and updated
- Working alongside product team to ensure that AI capabilities are built as democratized tools that
provides internal as well external stakeholders to innovate on top of it and make our customers
successful
- You will work closely with the Product & Engineering teams to convert the models into beautiful products
that will be used by thousands of Businesses everyday to transform their images and videos.

Job Requirements:

- 4-5 years of experience overall.
- Looking for strong Computer Vision experience and knowledge.
- BS/MS/ Phd degree in Computer Science, Engineering or a related subject from a ivy league institute
- Exposure on Deep Learning Techniques, TensorFlow/Pytorch
- Prior expertise on building Image processing applications using GANs, CNNs, Diffusion models
- Expertise with Image Processing Python libraries like OpenCV, etc.
- Good hands-on experience on Python, Flask or Django framework
- Authored publications at peer-reviewed AI conferences (e.g. NeurIPS, CVPR, ICML, ICLR,ICCV, ACL)
- Prior experience of managing teams and building large scale AI / CV projects is a big plus
- Great interpersonal and communication skills
- Critical thinker and problem-solving skills

Job Description – Data Science  

 

Basic Qualification:

• ME/MS from premier institute with a background in Mechanical/Industrial/Chemical/Materials engineering.
• Strong Analytical skills and application of Statistical techniques to problem solving
• Expertise in algorithms, data structures and performance optimization techniques
• Proven track record of demonstrating end to end ownership involving taking an idea from incubator to market
•   Minimum years of experience in data analysis (2+), statistical analysis, data mining, algorithms for optimization.

Responsibilities

The Data Engineer/Analyst will

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  
• Clear interaction with Business teams including product planning, sales, marketing, finance for defining the projects, objectives.
  
• Mine and analyze data from company databases to drive optimization and improvement of product and process development, marketing techniques and business strategies
  
• Coordinate with different R&D and Business teams to implement models and monitor outcomes.
  
• Mentor team members towards developing quick solutions for business impact.
  
• Skilled at all stages of the analysis process including defining key business questions, recommending measures, data sources, methodology and study design, dataset creation, analysis execution, interpretation and presentation and publication of results.
  

 

• 4+ years’ experience in MNC environment with projects involving ML, DL and/or DS
  
• Experience in Machine Learning, Data Mining or Machine Intelligence (Artificial Intelligence)
  
• Knowledge on Microsoft Azure will be desired.
  
• Expertise in machine learning such as Classification, Data/Text Mining, NLP, Image Processing, Decision Trees, Random Forest, Neural Networks, Deep Learning Algorithms
  
• Proficient in Python and its various libraries such as Numpy, MatPlotLib, Pandas
  
• Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to Business Teams.
  
• Experience in infra development / building platforms is highly desired.
  
• A drive to learn and master new technologies and techniques.
  

• 3+ years of Experience majoring in applying AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions.
• Programming skills in Python, knowledge in Statistics.
• Hands-on experience developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, parameter tuning, etc.). Familiarity with reinforcement learning is highly desirable.
• Experience in the financial domain and familiarity with financial models are highly desirable.
• Experience in image processing and computer vision.
• Experience working with building data pipelines.
• Good understanding of Data preparation, Model planning, Model training, Model validation, Model deployment and performance tuning.
• Should have hands on experience with some of these methods: Regression, Decision Trees,CART, Random Forest, Boosting, Evolutionary Programming, Neural Networks, Support Vector Machines, Ensemble Methods, Association Rules, Principal Component Analysis, Clustering, ArtificiAl Intelligence
• Should have experience in using larger data sets using Postgres Database. 

 

Hi ,

We have an Excellent job Opportunity for  "Applied Machine Learning Engineer" with one of thr Product based organization for Remote Working Mode or for Mumbai Location.

Job Responsibilities:

• Apply your knowledge of ML and statistics to conceptualise, experiment, develop & deploy machine learning & deep learning systems.
• Understanding the business objectives & defining the right target metrics to track performance & progress.
• Defining & building datasets with the appropriate representation techniques for learning.
• Training & tuning models. Running evaluation & test experiments on the models.
• Build ML pipelines end to end. (Everything MLOps.)
• Building pipelines for the various stages.
• Deploying models.
• Troubleshooting issues with models in production.
• Reporting results of model performance in production.
• Retraining, performance logging & maintenance.
• Help the business with insights for better decision-making. You will build many predictive models for internal business operations
  you will derive insights from the trained models & data to help the product & business teams make better decisions.

Requirements:

• 2+ years of work experience as an ML engineer or Data Scientist with a Bachelors Degree in Computer science or related field
• Theoretical & practical knowledge of Machine Learning, Deep Learning and Statistical methods. (NLP Tasks, Recommender Systems, Predictive Modelling etc)
• Since Pepper is a content company, you will work on many interesting text based problems. Solid understanding of Natural Language Processing techniques with Deep Learning is a must for this role.
• Familiarity with the popular NLP applications and text representation architectures & techniques: text classification, machine translation, named entity recognition, summarisation, question answering, zero-shot learning etc.  Bag of Words, TF-IDF, Word2vec, GloVe, BERT, ELMo, GPT etc.
• Experience with ML frameworks (like Tensorflow, Keras, PyTorch) & libraries like Sklearn.
• Experience with ML infrastructure & shipping models.
• Excellent programming & algorithmic skills. Good understanding of Data Structures and algorithms (fluent in at least one object oriented programming language). Proficiency in Python is a must.
• Strong understanding of database systems & schema design. Proficient in SQL

Please let us know if you are interested in the above opening and if interested please let us know your

 

Current CTC :

Expected CTC :

Notice Period :

Relevant experience in  Machine Learning :

Relevant experience in Deep Learning:

Relevant experience in NLP Applications:

 

Regards

Ashwini

About Turing:

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. 

Responsibilities:

• 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.

 

 

Minimum Requirements:

 

• 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.

Please apply if and only if you enjoy engineering, wish to write a lot of code, wish to do a lot of hands-on Python experimentation, already have in-depth knowledge of deep learning. This position is strictly for people having knowledge various Neural networks and can customize the neural network and not for people who have experience in downloading various AI/ML code.

This position is not for freshers. We are looking for candidates with AI/ML/CV experience of at least 4 year in the industry.

Responsibilities: 

• Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
• Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
• Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
• Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
• Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
• Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
• Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
• Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
• Drive analytics thought leadership and effectively contributes towards transformational initiatives.
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.

We are looking for applicants with a strong background in Analytics and Data mining (Web, Social and Big data), Machine Learning and Pattern Recognition, Natural Language Processing and Computational Linguistics, Statistical Modelling and Inferencing, Information Retrieval, Large Scale Distributed Systems and Cloud Computing, Econometrics and Quantitative Marketing, Applied Game Theory and Mechanism Design, Operations Research and Optimization, Human Computer Interaction and Information Visualization. Applicants with a background in other quantitative areas are also encouraged to apply.

We are looking for someone who can create and implement AI solutions. If you have built a product like IBM WATSON in the past and not just used WATSON to build applications, this could be the perfect role for you.

All successful candidates are expected to dive deep into problem areas of Zycus’ interest and invent technology solutions to not only advance the current products, but also to generate new product options that can strategically advantage the organization.

Skills:

• Experience in predictive modelling and predictive software development
• Skilled in Java, C++, Perl/Python (or similar scripting language)
• Experience in using R, Matlab, or any other statistical software
• Experience in mentoring junior team members, and guiding them on machine learning and data modelling applications
• Strong communication and data presentation skills

• Classification (svm, decision tree, random forest, neural network)
• Regression (linear, polynomial, logistic, etc)
• Classical Optimization(gradient descent, newton raphson, etc)
• Graph theory (network analytics)
• Heuristic optimisation (genetic algorithm, swarm theory)
• Deep learning (lstm, convolutional nn, recurrent nn)

Must Have:

• Experience: 3-9 years
• The ideal candidate must have proven expertise in Artificial Intelligence (including deep learning algorithms), Machine Learning and/or NLP
• The candidate must also have expertise in programming traditional machine learning algorithms, algorithm design & usage
• Preferred experience with large data sets & distributed computing in Hadoop ecosystem
• Fluency with databases

Software Engineer – ML at Indix provides an opportunity to design and build systems that crunch large amounts of data everyday What We’re Looking For- 3+ years of experience Ability to propose hypothesis and design experiments in the context of specific problems. Should come from a strong engineering background Good overlap with Indix Data tech stack such as Hadoop, MapReduce, HDFS, Spark, Scalding, Scala/Python/C++ Dedication and diligence in understanding the application domain, collecting/cleaning data and conducting experiments. Creativity in model and algorithm development. An obsession to develop algorithms/models that directly impact business. Master’s/Phd. in Computer Science/Statistics is a plus Job Expectations Experience working in text mining and python libraries like scikit-learn, numpy, etc Collect relevant data from production systems/Use crawling and parsing infrastructure to put together data sets. Survey academic literature and identify potential approaches for exploration. Craft, conduct and analyze experiments to evaluate models/algorithms. Communicate findings and take algorithms/models to production with end to end ownership.