Infosys

Machine Learning Engineer

Posted On

Oct. 1, 2024

Location

Bangalore, Karnataka

Experience Level

5 - 7 Years Exp.

Job Type

Permanent

Apply By

Dec. 31, 2024

Job Description

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. Educational Requirements Bachelor of Engineering Additional Responsibities: • 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. Technical and Professional 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.

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