Machine Learning Engineer

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