Machine Learning Engineer

Capgemini - Alpharetta, GA

Full-time - Mid Level

Alpharetta, GA

10,001+ employees

Professional, Scientific, and Technical Services

About the position

The Machine Learning Engineer at Capgemini will be responsible for designing, developing, and deploying machine learning models. This role requires extensive experience in handling complex data and utilizing various machine learning frameworks to create effective data pipelines and models. The position emphasizes collaboration and innovation within a supportive community, aiming to unlock the value of technology for leading organizations.

Responsibilities

• Design, develop, and deploy machine learning models using Python.
• Analyze complex, high-volume, high-dimensionality data for building data pipelines.
• Implement data preprocessing, imputation, and feature engineering techniques.
• Conduct exploratory data analysis and data visualization.
• Design and train machine learning models using TensorFlow or PyTorch.
• Perform model validation, fine-tuning, and hyperparameter tuning.
• Utilize transfer learning and existing CNN, LSTM models.
• Deploy models and manage inferencing processes using MLOPS, MFLOW, and Databricks.
• Develop NER models and REST APIs for model integration.
• Work with relational databases for data management.

Requirements

• 8+ years of experience in machine learning and data science.
• Proficient in Python and machine learning frameworks such as TensorFlow, Keras, or PyTorch.
• Experience in analyzing and processing high-dimensional data.
• Strong understanding of the ML lifecycle and data pipeline development.
• Knowledge of data augmentation and synthesis techniques.
• Experience with model design, training, and deployment.

Nice-to-haves

• Familiarity with MLOPS tools and practices.
• Experience with cloud platforms and data engineering tools.
• Knowledge of additional machine learning algorithms and techniques.

Benefits

• Flexible work arrangements.
• Comprehensive healthcare including dental, vision, and mental health programs.
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan.
• Paid time off and paid holidays.
• Paid parental leave.
• Family building benefits including adoption assistance and surrogacy.
• Social well-being benefits like subsidized child/elder care and tutoring.
• Access to mentoring, coaching, and learning programs.
• Participation in Employee Resource Groups.
• Disaster relief support.