Machine learning specialist

4 weeks ago

Bangalore, India Searce Inc Full time

About Searce Searce is a modern tech consulting firm that empowers clients to futurify their businesses, leveraging Cloud, AI & Analytics. We are a category defining niche’ cloud-native technology consulting company, specializing in modernizing (improve, automate & transform) the full-scope of infra, app, process & work. We partner with clients in their ‘beyond x’ journey to drive intelligent, impactful & futuristic business outcomes. We are the most preferred tech partner of choice when it comes to ‘solving for better’ for the new-age tech startups & digital enterprises, leading disruption in their industries. Our Service Offerings: We offer Advanced Cloud, Data & App Modernization, Cloud Consulting, Management & Improvement (Dev Ops, Sys Ops & Cloud Managed Services), Applied AI & Analytics services. As one of the top 5 niche’ full scope global partners for Google Cloud & a preferred partner for AWS, we are the most preferred ‘engineering-led’ tech company of choice when it comes to solving complex business problems. 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 Doc AI 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 Tensor Flow, 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

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