Machine Learning Engineer

Competetive Salary PF and Gratuity About Our Client Our client is an international professional services brand of firms, operating as partnerships under the brand. It is the second-largest professional services network in the world Job Description Position: ML Engineer Job type: Techno-Functional Preferred education qualifications: Bachelor/ Master's degree in computer science, Data Science, Machine Learning OR related technical degree Job location: India Geography: SAPMENA Required experience: 6-8 Years Preferred profile/ skills: 5+ years in developing and deploying enterprise-scale ML solutions (Mandatory) Proven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration), (Mandatory) Proficiency in Data Science/ML algorithms such as regression, classification, clustering, decision trees, random forest, gradient boosting, recommendation, dimensionality reduction (Mandatory) Experience in ML algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost) (Mandatory) Prior experience on MLOps with Kubeflow or TFX (Mandatory) Experience in model explainability with Shapley plot and data drift detection metrics. (Mandatory) Advanced programming skills with Python and SQL (Mandatory) Prior experience on building scalable ML pipelines & deploying ML models on Google Cloud (Mandatory) Proven expertise in ML pipeline optimization and monitoring the model's performance over time (Mandatory) Proficiency in version control systems such as GitHub Experience with feature engineering optimization and ML model fine tuning is preferred Google Cloud Machine Learning certifications will be a big plus Experience in Beauty or Retail/FMCG industry is preferred Experience in training with large volume of data (>100 GB) Experience in delivering AI-ML projects using Agile methodologies is preferred Proven ability to effectively communicate technical concepts and results to technical & business audiences in a comprehensive manner Proven ability to work proactively and independently to address product requirements and design optimal solutions Fluency in English, strong communication and organizational capabilities; and ability to work in a matrix/ multidisciplinary team Job objectives: Design, develop, deploy, and maintain data science and machine learning solutions to meet enterprise goals. Collaborate with product managers, data scientists & analysts to identify innovative & optimal machine learning solutions that leverage data to meet business goals. Contribute to development, rollout and onboarding of data scientists and ML use-cases to enterprise wide MLOps framework. Scale the proven ML use-cases across the SAPMENA region. Be responsible for optimal ML costs. Job description: Deep understanding of business/functional needs, problem statements and objectives/success criteria Collaborate with internal and external stakeholders including business, data scientists, project and partners teams in translating business and functional needs into ML problem statements and specific deliverables Develop best-fit end-to-end ML solutions including but not limited to algorithms, models, pipelines, training, inference, testing, performance tuning, deployments Review MVP implementations, provide recommendations and ensure ML best practices and guidelines are followed Act as 'Owner' of end-to-end machine learning systems and their scaling Translate machine learning algorithms into production-level code with distributed training, custom containers and optimal model serving Industrialize end-to-end MLOps life cycle management activities including model registry, pipelines, experiments, feature store, CI-CD-CT-CE with Kubeflow/TFX Accountable for creating, monitoring drifts leveraging continuous evaluation tools and optimizing performance and overall costs Evaluate, establish guidelines, and lead transformation with emerging technologies and practices for Data Science, ML, MLOps, Data Ops The Successful Applicant Position: ML Engineer Job type: Techno-Functional Preferred education qualifications: Bachelor/ Master's degree in computer science, Data Science, Machine Learning OR related technical degree Job location: India Geography: SAPMENA Required experience: 6-8 Years Preferred profile/ skills: 5+ years in developing and deploying enterprise-scale ML solutions (Mandatory) Proven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration), (Mandatory) Proficiency in Data Science/ML algorithms such as regression, classification, clustering, decision trees, random forest, gradient boosting, recommendation, dimensionality reduction (Mandatory) Experience in ML algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost) (Mandatory) Prior experience on MLOps with Kubeflow or TFX (Mandatory) Experience in model explainability with Shapley plot and data drift detection metrics. (Mandatory) Advanced programming skills with Python and SQL (Mandatory) Prior experience on building scalable ML pipelines & deploying ML models on Google Cloud (Mandatory) Proven expertise in ML pipeline optimization and monitoring the model's performance over time (Mandatory) Proficiency in version control systems such as GitHub Experience with feature engineering optimization and ML model fine tuning is preferred Google Cloud Machine Learning certifications will be a big plus Experience in Beauty or Retail/FMCG industry is preferred Experience in training with large volume of data (>100 GB) Experience in delivering AI-ML projects using Agile methodologies is preferred Proven ability to effectively communicate technical concepts and results to technical & business audiences in a comprehensive manner Proven ability to work proactively and independently to address product requirements and design optimal solutions Fluency in English, strong communication and organizational capabilities; and ability to work in a matrix/ multidisciplinary team Job objectives: Design, develop, deploy, and maintain data science and machine learning solutions to meet enterprise goals. Collaborate with product managers, data scientists & analysts to identify innovative & optimal machine learning solutions that leverage data to meet business goals. Contribute to development, rollout and onboarding of data scientists and ML use-cases to enterprise wide MLOps framework. Scale the proven ML use-cases across the SAPMENA region. Be responsible for optimal ML costs. Job description: Deep understanding of business/functional needs, problem statements and objectives/success criteria Collaborate with internal and external stakeholders including business, data scientists, project and partners teams in translating business and functional needs into ML problem statements and specific deliverables Develop best-fit end-to-end ML solutions including but not limited to algorithms, models, pipelines, training, inference, testing, performance tuning, deployments Review MVP implementations, provide recommendations and ensure ML best practices and guidelines are followed Act as 'Owner' of end-to-end machine learning systems and their scaling Translate machine learning algorithms into production-level code with distributed training, custom containers and optimal model serving Industrialize end-to-end MLOps life cycle management activities including model registry, pipelines, experiments, feature store, CI-CD-CT-CE with Kubeflow/TFX Accountable for creating, monitoring drifts leveraging continuous evaluation tools and optimizing performance and overall costs Evaluate, establish guidelines, and lead transformation with emerging technologies and practices for Data Science, ML, MLOps, Data Ops