11+ Unsupervised learning Jobs in India

• Research and test novel machine learning approaches for analysing large-scale distributed computing applications.
• Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy,  efficacy, and robustness
• Work closely with other functional teams to integrate implemented systems into the SaaS platform
• Suggest innovative and creative concepts and ideas that would improve the overall platform

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The ideal candidate must have the following qualifications:

• 5 + years experience in practical implementation and deployment of large customer-facing ML based systems.
• MS or M Tech (preferred) in applied mathematics/statistics;  CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills
• In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python is a must
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

Most importantly, you should be someone who is passionate about building new and innovative products that solve tough real-world problems.

Chennai, India

About Kloud9:

Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.

Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.

At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.

Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.

We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.

Responsibilities:

●       Studying, transforming, and converting data science prototypes

●       Deploying models to production

●       Training and retraining models as needed

●       Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their respective scores

●       Analyzing the errors of the model and designing strategies to overcome them

●       Identifying differences in data distribution that could affect model performance in real-world situations

●       Performing statistical analysis and using results to improve models

●       Supervising the data acquisition process if more data is needed

●       Defining data augmentation pipelines

●       Defining the pre-processing or feature engineering to be done on a given dataset

●       To extend and enrich existing ML frameworks and libraries

●       Understanding when the findings can be applied to business decisions

●       Documenting machine learning processes

Basic requirements: 

●       4+ years of IT experience in which at least 2+ years of relevant experience primarily in converting data science prototypes and deploying models to production

●       Proficiency with Python and machine learning libraries such as scikit-learn, matplotlib, seaborn and pandas

●       Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc

●       Experience in working with ML frameworks like TensorFlow, Keras, OpenCV

●       Strong written and verbal communications

●       Excellent interpersonal and collaboration skills.

●       Expertise in visualizing and manipulating big datasets

●       Familiarity with Linux

●       Ability to select hardware to run an ML model with the required latency

●       Robust data modelling and data architecture skills.

●       Advanced degree in Computer Science/Math/Statistics or a related discipline.

●       Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.)

Nice to have

●       Familiarity with Java, and R code writing.

●       Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world

●       Verifying data quality, and/or ensuring it via data cleaning

●       Supervising the data acquisition process if more data is needed

●       Finding available datasets online that could be used for training

Why Explore a Career at Kloud9:

With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.

ADF Developer with top Conglomerates for Kochi location_ Air India

conducting F2F Interviews on 22nd April 2023

Experience - 2-12 years.

Location - Kochi only (work from the office only)

Notice period - 1 month only.

If you are interested, please share the following information at your earliest

A proficient, independent contributor that assists in technical design, development, implementation, and support of data pipelines; beginning to invest in less-experienced engineers.

Responsibilities:

- Design, Create and maintain on premise and cloud based data integration pipelines. 
- Assemble large, complex data sets that meet functional/non functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
- Build analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Create data pipelines to enable BI, Analytics and Data Science teams that assist them in building and optimizing their systems
- Assists in the onboarding, training and development of team members.
- Reviews code changes and pull requests for standardization and best practices
- Evolve existing development to be automated, scalable, resilient, self-serve platforms
- Assist the team in the design and requirements gathering for technical and non technical work to drive the direction of projects

Technical & Business Expertise:

-Hands on integration experience in SSIS/Mulesoft
- Hands on experience Azure Synapse
- Proven advanced level of writing database experience in SQL Server
- Proven advanced level of understanding about Data Lake
- Proven intermediate level of writing Python or similar programming language
- Intermediate understanding of Cloud Platforms (GCP) 
- Intermediate understanding of Data Warehousing
- Advanced Understanding of Source Control (Github)

Role Summary

We Are looking for an analytically inclined, Insights Driven Product Analyst to make our organisation more data driven. In this role you will be responsible for creating dashboards to drive insights for product and business teams. Be it Day to Day decisions as well as long term impact assessment, Measuring the Efficacy of different products or certain teams, You'll be Empowering each of them. The growing nature of the team will require you to be in touch with all of the teams at upgrad. Are you the "Go-To" person everyone looks at for getting Data, Then this role is for you.

Roles & Responsibilities

• Lead and own the analysis of highly complex data sources, identifying trends and patterns in data and provide insights/recommendations based on analysis results
• Build, maintain, own and communicate detailed reports to assist Marketing, Growth/Learning Experience and Other Business/Executive Teams
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
• Analyze data and generate insights in the form of user analysis, user segmentation, performance reports, etc.
• Facilitate review sessions with management, business users and other team members
• Design and create visualizations to present actionable insights related to data sets and business questions at hand
• Develop intelligent models around channel performance, user profiling, and personalization

Skills Required

• Having 4-6 yrs hands-on experience with Product related analytics and reporting
• Experience with building dashboards in Tableau or other data visualization tools such as D3
• Strong data, statistics, and analytical skills with a good grasp of SQL.
• Programming experience in Python is must
• Comfortable managing large data sets
• Good Excel/data management skills

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.

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 2+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor, etc)
• strong quantitative and programming skills with a product-driven sensibility