AI ML Engineer

Infosys Consulting is the worldwide management and IT consultancy unit of the Infosys Group (NYSE: INFY), a global advisor to leading companies for strategy, process engineering and technology-enabled transformation programs.

We partner with clients to design and implement customized solutions to address their complex business challenges, and to help them in a post-modern ERP world. By combining innovative and human-centric approaches with the latest technological advances, we enable organizations to reimagine their future and create sustainable and lasting business value.

A pioneer in breaking down the barriers between strategy and execution, Infosys Consulting delivers superior business value to its clients by advising them on strategy, process optimization, and IT-enabled transformation. To find out how we go beyond the expected to deliver the exceptional, visit us at www.infosysconsultinginsights.com Infosys Consulting – is a real consultancy for real consultants.

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• Proven experience as an AI/ML Engineer or similar role.
• Strong programming skills in Python, R, or similar languages.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
• Proficiency in data manipulation and analysis using tools like Pandas, NumPy, and SQL.
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills to effectively convey technical concepts to non-technical stakeholders.

• Experience with natural language processing (NLP) and computer vision.
• Knowledge of big data technologies such as Hadoop, Spark, and Kafka.
• Understanding of software development best practices, including version control (Git) and CI/CD pipelines.
• Experience with A/B testing and experimental design.

• →Design, develop, and implement machine learning models and algorithms to solve business problems.
• →Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• →Conduct data preprocessing, feature engineering, and model evaluation to ensure high performance and accuracy.
• →Deploy and maintain machine learning models in production environments.
• →Continuously monitor and improve model performance through iterative testing and optimization.
• →Stay up-to-date with the latest advancements in AI and ML technologies and integrate them into existing projects.
• →Document processes, models, and experiments to ensure reproducibility and knowledge sharing within the team.