Head AI Ination EdTech

Job Description

Key activities & responsibilities :- This is a business-technology-domain focused result-oriented role aimed at bringing the cutting edge of AI technology and research to the forefront of business by building tangible proof-of-concepts, products, utilities, automated processes and playbooks.- This role will work closely with the CEO to position the underpinning science and IP of the Platform as the basis of future fundraising and investment initiatives. As such, you will be an excellent communicator of technical ideas to non-technical audiences and a resourceful and creative manager who can deliver big ideas with the resource envelope of a start-up.- You will be a highly technical player, with the ability to research and come up with impactful ideas across AI/ML, NLP, Knowledge graph (and other statistical, quantitative and engineering techniques) and build scalable and efficient solutions and/or implementation playbook for business application.- You will be comfortable operating in a fast paced, results driven environment with watertight deadlines and producing measurable and tangible outcome.- You should be able to independently lead projects and work with business stakeholders, data engineering and technology teams to bring solutions to fruition.- You should be able to guide others working alongside in same or similar research projects and document findings and learnings in a scientific way.- You would research and create proof of concept products, solutions, playbooks, etc. on topics including (and not limited to) NLP, NLG, Deep Learning, Reinforcement Learning, GANs, Active Learning, Knowledge Graph on various application areas like Education, Learning, Career management, Workforce, Talent management etc- You will evangelize and advocate about the developed AI POCs, products and solutions across business and broader team - drive adoption- You are required to work individually or as part of a team on data science and/or engineering problems and work closely with business partners across the organizationQualifications and Experience : Must haves :- Masters in machine learning, information science, engineering, statistics or a highly quantitative field with industry work experience- Proven ability to relate to and solve business problems through machine learning and statistics- 15+ years of hands-on experience developing and implementing machine learning algorithms and/or statistical models or with engineering fields- Strong collaboration skills- Work effectively in a matrixed environment- Should be able to find ways to identify and secure resources if required- Experience in developing models and solutions using both standard and advanced AI/ML techniques like Deep Learning, Reinforcement Learning, GANs, graphical models, etc.- Deep knowledge in areas such as Knowledge Graph modelling, AI/ML driven search applications, document Q&A systems, Chatbots, fairness/bias in AI models, Causal inference, etc.- Experience in developing NLP/NLG models across fields of topic modelling, text mining, documents, speech, etc. Experience in advanced concepts like Transformers is a bonus- Strong programming skills using Python Java, Shell scripting, etc.- Proven experience in leveraging open-source AI/ML packages (including names such as Tensorflow, Keras, Pytorch, NLTK, TextBlob, SpaCy, AllenNLP, MonkeyLearn, Hugging face, BERT, GPT-3, etc.)- Experience with third-party/vendor AI/ML capabilities like Neo4J, IBM Watson, Snorkel, Lucid, etc.- Experience in one or more of Big Data skills - SQL, Aster, Teradata, Hadoop, SPARKBenefits :- We are a Cloud SaaS Company, and our products are created by using the latest technologies like ML and AI. - Highly flexible and full time remote working options- You get to work and deal with our global customers and partners- Very competitive compensation and benefits for deserving candidate- Highly dynamic and fast paced work culture with a lot of opportunity to learn, grow and achieve.,

Keyskills :
proof of conceptsource system analysisbig datatext miningdata sciencedeep learningshell scriptingactive learningmachine learningcausal inference