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Manager - Applied AI / Machine Learning
2 months ago
Job Responsibilities
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
- Managing available resources such as hardware, data, and personnel so that deadlines are met
- Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
- 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
- Knowledge sharing with the team to adopt best practices, actively contribute to and re-use community best practices
- 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
- Defining validation strategies
- Understanding DocAI and vision API
- Architect, build, maintain, and improve new and existing suite of algorithms and their underlying systems
- Defining the preprocessing or feature engineering to be done on a given dataset
- Establishing scalable, efficient, automated processes for data analyses, model development
- Utilizing your entrepreneurial spirit to identify new opportunities to optimize business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset
- Defining data augmentation pipelines
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Deploying models to production
- Knowledge and understanding of GCP Ecosystem
Qualification
- BE/B.Tech/Masters in a quantitative field such as CS, EE, Information sciences, Statistics, Mathematics, Economics, Operations Research, or related, with focus on applied and foundational Machine Learning , AI , NLP and/or / data-driven statistical analysis & modelling
- 4+ years of Experience majorly in applying AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions to multiple domains, including financial engineering, financial processes a plus
- Strong, proven programming skills and with machine learning and deep learning and Big data frameworks including TensorFlow, Caffe, Spark, Hadoop.
- Experience with writing complex programs and implementing custom algorithms in these and other environments
- Experience beyond using open source tools as-is, and writing custom code on top of, or in addition to, existing open source frameworks
- Proven capability in demonstrating successful advanced technology solutions (either prototypes, POCs, well-cited research publications, and/or products) using ML/AI/NLP/data science in one or more domains
- Research and implement novel machine learning and statistical approaches
- Experience in data management, data analytics middleware, platforms and infrastructure, cloud and fog computing is a plus
- Excellent communication skills (oral and written) to explain complex algorithms, solutions to stakeholders across multiple disciplines, and ability to work in a diverse team
