Searce Inc | Machine Learning Specialist

7 hours ago


Delhi, India Searce Inc Full time
About SearceSearce is a modern tech consulting firm that empowers clients to futurify theirbusinesses, 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 (DevOps, SysOps & 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 ResponsibilitiesUnderstanding business objectives and developing models that help to achievethem, along with metrics to track their progressManaging available resources such as hardware, data, and personnel so that deadlines are metAnalyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probabilityExploring 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 worldKnowledge sharing with the team to adopt best practices, actively contribute to and re-use community best practicesVerifying data quality, and/or ensuring it via data cleaningSupervising the data acquisition process if more data is neededFinding available datasets online that could be used for trainingDefining validation strategiesUnderstanding DocAI and vision APIArchitect, build, maintain, and improve new and existing suite of algorithms andtheir underlying systemsDefining the preprocessing or feature engineering to be done on a givendatasetEstablishing scalable, efficient, automated processes for data analyses, modeldevelopmentUtilizing 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 mindsetDefining data augmentation pipelinesTraining models and tuning their hyperparametersAnalyzing the errors of the model and designing strategies to overcome themDeploying models to productionKnowledge and understanding of GCP Ecosystem

QualificationBE/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 & modelling4+ 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 plusStrong, 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 environmentsExperience beyond using open source tools as-is, and writing custom code on top of, or in addition to, existing open source frameworksProven 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 domainsResearch and implement novel machine learning and statistical approachesExperience in data management, data analytics middleware, platforms and infrastructure, cloud and fog computing is a plusExcellent 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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