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.
Similar jobs
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.
TOP 3 SKILLS
Python (Language)
Spark Framework
Spark Streaming
Docker/Jenkins/ Spinakar
AWS
Hive Queries
He/She should be good coder.
Preff: - Airflow
Must have experience: -
Python
Spark framework and streaming
exposure to Machine Learning Lifecycle is mandatory.
Project:
This is searching domain project. Any searching activity which is happening on website this team create the model for the same, they create sorting/scored model for any search. This is done by the data
scientist This team is working more on the streaming side of data, the candidate would work extensively on Spark streaming and there will be a lot of work in Machine Learning.
INTERVIEW INFORMATION
3-4 rounds.
1st round based on data engineering batching experience.
2nd round based on data engineering streaming experience.
3rd round based on ML lifecycle (3rd round can be a techno-functional round based on previous
feedbacks otherwise 4th round will be a functional round if required.
About Quadratyx:
We are a product-centric insight & automation services company globally. We help the world’s organizations make better & faster decisions using the power of insight & intelligent automation. We build and operationalize their next-gen strategy, through Big Data, Artificial Intelligence, Machine Learning, Unstructured Data Processing and Advanced Analytics. Quadratyx can boast more extensive experience in data sciences & analytics than most other companies in India.
We firmly believe in Excellence Everywhere.
Job Description
Purpose of the Job/ Role:
• As a Technical Lead, your work is a combination of hands-on contribution, customer engagement and technical team management. Overall, you’ll design, architect, deploy and maintain big data solutions.
Key Requisites:
• Expertise in Data structures and algorithms.
• Technical management across the full life cycle of big data (Hadoop) projects from requirement gathering and analysis to platform selection, design of the architecture and deployment.
• Scaling of cloud-based infrastructure.
• Collaborating with business consultants, data scientists, engineers and developers to develop data solutions.
• Led and mentored a team of data engineers.
• Hands-on experience in test-driven development (TDD).
• Expertise in No SQL like Mongo, Cassandra etc, preferred Mongo and strong knowledge of relational databases.
• Good knowledge of Kafka and Spark Streaming internal architecture.
• Good knowledge of any Application Servers.
• Extensive knowledge of big data platforms like Hadoop; Hortonworks etc.
• Knowledge of data ingestion and integration on cloud services such as AWS; Google Cloud; Azure etc.
Skills/ Competencies Required
Technical Skills
• Strong expertise (9 or more out of 10) in at least one modern programming language, like Python, or Java.
• Clear end-to-end experience in designing, programming, and implementing large software systems.
• Passion and analytical abilities to solve complex problems Soft Skills.
• Always speaking your mind freely.
• Communicating ideas clearly in talking and writing, integrity to never copy or plagiarize intellectual property of others.
• Exercising discretion and independent judgment where needed in performing duties; not needing micro-management, maintaining high professional standards.
Academic Qualifications & Experience Required
Required Educational Qualification & Relevant Experience
• Bachelor’s or Master’s in Computer Science, Computer Engineering, or related discipline from a well-known institute.
• Minimum 7 - 10 years of work experience as a developer in an IT organization (preferably Analytics / Big Data/ Data Science / AI background.
- Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
- Good understanding of the underlying business and workings of cross functional teams for successful execution
- Design and develop analyses based on business requirement needs and challenges.
- Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
- Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
- Identify and use appropriate investigative and analytical technologies to interpret and verify results.
- Apply and learn a wide variety of tools and languages to achieve results
- Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.
Requirements
- 2 - 4 years of relevant experience in Data science.
- Preferred education: Bachelor's degree in a technical field or equivalent experience.
- Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
- Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
- Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
- Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
- Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
- Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
- Experience in risk and credit score domains preferred.
About the Role:
As a Speech Engineer you will be working on development of on-device multilingual speech recognition systems.
- Apart from ASR you will be working on solving speech focused research problems like speech enhancement, voice analysis and synthesis etc.
- You will be responsible for building complete pipeline for speech recognition from data preparation to deployment on edge devices.
- Reading, implementing and improving baselines reported in leading research papers will be another key area of your daily life at Saarthi.
Requirements:
- 2-3 year of hands-on experience in speech recognitionbased projects
- Proven experience as a Speech engineer or similar role
- Should have experience of deployment on edge devices
- Candidate should have hands-on experience with open-source tools such as Kaldi, Pytorch-Kaldi and any of the end-to-end ASR tools such as ESPNET or EESEN or DeepSpeech Pytorch
- Prior proven experience in training and deployment of deep learning models on scale
- Strong programming experience in Python,C/C++, etc.
- Working experience with Pytorch and Tensorflow
- Experience contributing to research communities including publications at conferences and/or journals
- Strong communication skills
- Strong analytical and problem-solving skills
Specialism- Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, python, decision tree, random forest, SAS, clustering classification
Senior Analytics Consultant- Responsibilities
- Understand business problem and requirements by building domain knowledge and translate to data science problem
- Conceptualize and design cutting edge data science solution to solve the data science problem, apply design thinking concepts
- Identify the right algorithms , tech stack , sample outputs required to efficiently adder the end need
- Prototype and experiment the solution to successfully demonstrate the value
Independently or with support from team execute the conceptualized solution as per plan by following project management guidelines - Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization
- Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development , practice development initiatives
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
Must-have skills
- 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
Benefits
- 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.
Basic Qualifications:
∙Bachelors in Computer Science/Mathematics + Research (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from Tier1 tech institutes.
∙3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems.
∙1 year or more of experience specifically with deep learning (CNN, RNN, LSTM, RBM etc).
∙Strong working knowledge of deep learning, machine learning, and statistics.
- Deep domain understanding of Personalization, Search and Visual.
∙Strong math skills with statistical modeling / machine learning.
∙Hands-on experience building models with deep learning frameworks like MXNet or Tensorflow.
∙Experience in using Python, statistical/machine learning libs.
∙Ability to think creatively and solve problems.
∙Data presentation skills.
Preferred:
∙MS/ Ph.D. (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from IISc and other Top Global Universities.
∙Or, Publications in highly accredited journals (If available, please share links to your published work.).
∙Or, history of scaling ML/Deep learning algorithm at massively large scale.
· Advanced Spark Programming Skills · Advanced Python Skills · Data Engineering ETL and ELT Skills · Expertise on Streaming data · Experience in Hadoop eco system · Basic understanding of Cloud Platforms · Technical Design Skills, Alternative approaches |
· Hands on expertise on writing UDF’s · Hands on expertise on streaming data ingestion · Be able to independently tune spark scripts · Advanced Debugging skills & Large Volume data handling. · Independently breakdown and plan technical Tasks |