AI Engineer

This role is primarily responsible for building AIML models and cognitive applications

Principal Accountabilities :

1. Good in communication and converting business requirements to functional requirements

2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data

3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.

5. Experience in SOTA Deep Learning techniques to solve NLP problems.

6. End-to-end data collection, model development and testing, and integration into production environments.

7. Build and prototype analysis pipelines iteratively to provide insights at scale.

8. Experience in querying different data sources

9. Partner with developers and business teams for the business-oriented decisions

10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.

Responsibilities

• Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
• Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
• Own the end-end process, from recognizing the problem to implementing the solution.
• Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
• Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.

Skills and Qualification

• 12 to 15 yrs of experience.
• An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
• Experience with text mining, parsing, and classification using state-of-the-art techniques.
• Experience with information retrieval, Natural Language Processing, Natural Language
• Understanding and Neural Language Modeling.
• Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
• Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
• Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
• Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.

Key Skills
o Convert machine learning models into APIs for applications accessibility
o Running machine learning tests and experiments
o Implementing appropriate ML algorithms
o Creating machine learning models and retraining systems
o Study and transform data science prototypes
o Design machine learning systems
o Research and implement appropriate ML algorithms and tools
o Train and retrain systems when necessary
o Test and deploy models
o Use AI to empower the company with novel capabilities
o Designing and developing machine learning and deep learning system
o Outstanding analytical and problem-solving skills
• Alexa
o Excellent in Python programming
o Experience with AWS Lamda
o Experience with Alexa skills
o Alexa skill directives
• Google
o Excellent in NodeJS programming
o Experience with GCP - Dialog Flow and Actions on Google
o Using built-in intents and developing custom intents
o API integration and Postman knowledge

 

What you need to have:

Role Description: The Chatbot Developer will develop software and system architecture while ensuring alignment with enterprise technology standards (e.g., solution patterns, application frameworks).

Responsibilities:

- Develop REST/JSON API’s Design code for high scale/availability/resiliency.

- Develop responsive web apps and integrate APIs using NodeJS.

- Presenting Chat efficiency reports to higher Management

- Develop system flow diagrams to automate a business function and identify impacted systems; metrics to depict the cost benefit analysis of the solutions developed.

- Work closely with business operations to convert requirements into system solutions and collaborate with development teams to ensure delivery of highly scalable and available systems.

- Using tools to classify/categorize the chat based on intents and coming up with F1 score for Chat Analysis

- Experience in analyzing real agents Chat conversation with agent to train the Chatbot.

- Developing Conversational Flows in the chatbot

- Calculating Chat efficiency reports.

Good to Have:

- Monitors performance and quality control plans to identify performance. 

- Works on problems of moderate and varied complexity where analysis of data may require adaptation of standardized practices. 

- Works with management to prioritize business and information needs.

- Experience in analyzing real agents Chat conversation with agent to train the Chatbot.

- Identifies, analyzes, and interprets trends or patterns in complex data sets.

- Ability to manage multiple assignments.

- Understanding of ChatBot Architecture.

- Experience of Chatbot training

A research lab with roots laid in innovation, we are looking for someone who can take reins of our AI based development think tank. Given the work ethics and results, the salary can be re-negotiated in 5 months.

We at artivatic are seeking passionate, talented and research focused natural processing language engineer with strong machine learning and mathematics background to help build industry-leading technology. - The ideal candidate will have research/implementation experience modeling and developing NLP tools and experience working with machine learning/deep learning algorithms.Qualifications :- Bachelors or Master degree in Computer Science, Mathematics or related field with specialization in natural language processing, Machine Learning or Deep Learning.- Publication record in conferences/journals is a plus.- 2+ years of working/research experience building NLP based solutions is preferred.Required Skills :- Hands-on Experience building NLP models using different NLP libraries ad toolkit like NLTK, Stanford NLP etc.- Good understanding of Rule-based, Statistical and probabilistic NLP techniques.- Good knowledge of NLP approaches and concepts like topic modeling, text summarization, semantic modeling, Named Entity recognition etc.- Good understanding of Machine learning and Deep learning algorithms.- Good knowledge of Data Structures and Algorithms.- Strong programming skills in Python/Java/Scala/C/C++.- Strong problem solving and logical skills.- A go-getter kind of attitude with a willingness to learn new technologies.- Well versed with software design paradigms and good development practices.Responsibilities :- Developing novel algorithms and modeling techniques to advance the state of the art in Natural Language Processing.- Developing NLP based tools and solutions end to end.

As a Senior Consultant Analytics, you shall gather, analyze, identify and lead actionable data insights to solve real complex challenges. Your work will directly influence decisions taken to build the most successful web/mobile gaming platform with games played by millions across the world. Responsibilities Leverage complex data algorithms and numerical methods for forecasting, simulation, and predictive analysis, designed to optimize key decisions and metrics such as retention, engagement, and operations. Work with all teams in the company to understand, plan and drive data-based actionable decisions, championing the Data Science culture. Analyze consumer data to drive insight on how to target effectively, retain customers at low cost, and optimize engagement metrics. Develop a reporting process for all KPIs. Recruit, develop and coach talent. Champion awareness of data indicators within the organization and teach everyone to proactively identify data patterns, growth trends, and areas for improvement. Qualifications B.tech or Bachelor degree in Data science. An MBA or advanced degree in a quantitative discipline is preferred. 3+ years in Data Science and Analytics execution, with specific experience in all stages - gathering, hygiene, and analysis of data resulting in actionable insights for an end-to-end product, marketing and business operations. Knowledge of advanced analytics including but not limited to Regression, GLMs, survival modeling, predictive analytics, forecasting, machine learning, decision trees etc. Past experience in at least one Statistical and analytic tools or language expertise R, Python, SAS etc.. Expertise in analysis Algorithms, Numerical Methods and Data Tactics used to drive operational excellence, user engagement and retention. Expertise in at least one visualization platforms such as Tableau, QlikView, Spotfire and Excel. Tableau skills preferred. Advanced SQL is mandatory skills. Ability to creatively solve business problems through innovative approaches. Ability to work with various teams in a complex environment, ensuring timely delivery of multiple projects. Highly analytical with the ability to collate, analyze and present data, and drive clear insights into decisions that improve KPIs. Ability to effectively communicate and manage relationships with senior management, company divisions and partners.

Data [email protected] Data Science at Dream11 comprises of enthusiastic young scientists thriving to derive value from data continuously. Data Science team focuses on product and user analytics by integrating data from multiple sources streaming at a rate of ~100 GB/day. The team has developed state-of-art solutions for developing automated contests, data driven risk prevention model, risk aversion, recommendation systems to enhance product and user experience. Your Role: You should be self-motivated to develop data science solutions, practices and lead data science team in Mumbai at Dream11. The role involves intense usage of machine learning, predictive modelling, data mining, behaviour psychology and sports analytics to help Dream11 be more fun, social and rewarding. • Responsibility for developing data science road map and initiatives at Dream11 • Giving a strategic perspective to our teams and providing business understanding to the organisation based on your data analysis • Developing data science solutions to enhance product ability and user experience • Applying rigorous experimentation and iterative analytics to steer the improvements of our products, while implementing machine learning and artificial intelligence • Creating algorithms to extract information from a large data set to perform statistical analysis and analyse the same to create predictive models for consumer behaviour • Establishing scalable, efficient, automated processes for model development, model validation and model implementation MUST have: • You need to eat, breathe and sleep data. For you, everything must be probability and distributions • Have a strong background in statistical concepts and machine learning models along with an expertise in data visualization and presentation • Have 5+ years of work experience in Data Sciences and Machine Learning. • Have 8+ years of work experience with large volumes of data preferably in e-commerce • Have a formal education in relevant fields such as stats, computer science or applied math Bonus: • Managed a team • Experience of working in an agile environment • Previous experience at a fast-growing consumer internet startup

Primary Skills : - B.Tech/MS/PhD degree in Computer Science, Computer Engineering or related technical discipline with 3-4 years of industry experience in Data Science. - Proven experience of working on unstructured and textual data. Deep understanding and expertise of NLP techniques (POS tagging, NER, Semantic role labelling etc). - Experience working with some of the supervised/unsupervised learning ML models such as linear/logistic regression, clustering, support vector machines (SVM), neural networks, Random Forest, CRF, Bayesian models etc. The ideal candidate will have a wide coverage of the different methods/models, and an in depth knowledge of some. - Strong coding experience in Python, R and Apache Spark. Python Skills are mandatory. - Experience with NoSQL databases, such as MongoDB, Cassandra, HBase etc. - Experience of working with Elastic search is a plus. - Experience of working on Microsoft Azure is a plus although not mandatory. - Basic knowledge of Linux and related scripting like Bash/shell script. Role Description (Roles & Responsibilities) : - Candidate will research, design and implement state-of-the-art ML systems using predictive modelling, deep learning, natural language processing and other ML techniques to help meeting business objectives. - Candidate will work closely with the product development/Engineering team to develop solutions for complex business problems or product features. - Handle Big Data scale for training and deploying ML/NLP based business modules/chatbots.