AI/ML Lead

3 weeks ago

india Havells India Ltd Full time

Company: Havells India Ltd

Role: AI/ML Lead

Experience: 4 to 8years

Location: Bangalore

Qualification: B.E/B.Tech/M.E/M.Tech


Job Description for ML Research Engineer


RESPONSIBILITIES: • Delivering an end-to-end solution, starting with requirements comprehension, developing research proposals, implementing the research by experimenting with various methodologies and algorithms, documenting, and presenting outcomes. • Utilize programming, data modelling, analytical and statistical techniques to analyse vast amounts of data and produce insights that can be put to use. • Create and test hypotheses, then plan experiments to address specific, challenging questions. • Project documentation includes corporate goals, data collection and processing procedures, leading strategies, the final algorithm, and a comprehensive list of outcomes and analytical metrics. • Establish best practises and procedures, share information with the team, mentor more junior team members, and contribute to the shared code library. • Take ownership of your tasks and have end to end responsibility from planning stage to presenting results


QUALIFICATIONS: • At least 5+ years of working experience in development with at least 4+ years of relevant experience in developing AI/ML based solutions • At least 4+ years of hands-on data science experience using Python for data analytics, visualization, statistical programming and data mining for problem-solving. Domain knowledge and experience in Internet of Things (IoT) is a plus. • Demonstrated expertise in managing end-to-end research POCs, including the design, execution, analysis, and conclusions of your research, techniques, and outcomes. • Excellent understanding of data science, machine learning, deep learning (CV, NLP) techniques, algorithms, and toolkits to develop and deploy scalable solutions for production. • Applied mathematical and statistical skills, such as statistical analysis, distributions, multivariate testing, regression, classification, and optimization algorithms, etc. to create, test, analyse, and explain results. • Well familiar with Edge computing and neural networks using Tensorflow Lite, TinyML. • Familiar with MLOps tools like MLflow or Kubeflow, deep learning frameworks like TensorFlow, or Pytorch. • Working experience with big data systems (Hadoop, Spark, Hive) is an advantage.


OTHER SKILLS: • Excellent communication abilities, including the capacity to translate complicated technical concepts and convey their significance to a variety of audiences. • Having the ability to turn corporate objectives into analysis that can be used. • A track record of working with teams who are spread out geographically • Should be a self-starter with a high level of initiative.

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