Machine Learning Engineer

Key Responsibilities:

• Responsibilities
• As part of this role you ll need to comprehend various ML algorithms their strengths weaknesses and how they impact deployment
• Algorithm Development
• Design develop and implement machine learning algorithms to address specific business challenges
• Collaborate with cross functional teams to understand requirements and deliver solutions that meet business objectives
• Data Analysis and Modeling
• Perform exploratory data analysis to gain insights and identify patterns in large datasets
• Build validate and deploy machine learning models for predictive and prescriptive analytics
• Feature Engineering
• Extract and engineer relevant features from diverse datasets to enhance model performance
• Optimize and fine tune models for improved accuracy and efficiency
• Model Evaluation and Deployment
• Conduct thorough evaluation of machine learning models using appropriate metrics
• Deploy models into production environments ensuring scalability reliability and performance
• Communicate complex technical concepts to non technical stakeholders effectively

Technical Requirements:

• Bachelor s or Master s degree in Computer Science Machine Learning Data Science or a related field
• 5 6 years of hands on experience in developing and deploying machine learning models
• Proficiency in programming languages such as Python R or Java
• Experience with data preprocessing feature engineering and model evaluation techniques
• Understanding how to set up scalable and reliable environments for ML models is crucial
• Mastery of CI CD and Automation Tools Continuous Integration Continuous Deployment
• Knowledge of tools like Azure ML DevOps Jenkins GitLab CI CD and Kubernetes to automate workflows and ensure smooth deployments
• Knowledge of Monitoring and Logging Systems Azure Monitor Prometheus Grafana and ELK stack for monitoring and logging
• Strong Communication and Collaboration Abilities As a team lead the candidate will work closely with data scientists engineers and stakeholders

Additional Responsibilities:

• Understanding of forecasting revenue ERP environments e
• g
• Salesforce SAP ECC
• Knowledge of machine learning frameworks e
• g
• TensorFlow PyTorch and libraries e
• g
• scikit learn
• Deep Understanding of Machine Learning Models
• Proficiency in Cloud and On Premises Infrastructure
• Excellent communication skills for aligning goals resolving conflicts and driving successful ML projects
• Continuous Learning Stay abreast of the latest developments in machine learning data science and related fields

Preferred Skills: