Senior Associate, Agents/Chatbots IC

What you will do

In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production

• Collaborate with data scientists to develop, train, and evaluate machine learning models.
• Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.
• Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.
• Implement DevOps/MLOps standards to automate ML workflows and improve efficiency.
• Develop and implement monitoring systems to track model performance and identify issues.
• Conduct A/B testing and experimentation to optimize model performance.
• Work closely with data scientists, engineers, and product teams to deliver ML solutions.
• Stay updated with the latest trends and advancements

We are all different, yet we all use our unique contributions to serve patients. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.

Basic Qualifications:

• Masters degree with 5+ years of experience in Computer Science, IT or related field

• Bachelors degree with 5-9 years of experience in Computer Science, IT or related field
• Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.

Preferred Qualifications:

• Solid foundation in machine learning algorithms and techniques
• Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)
• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
• Outstanding analytical and problem-solving skills; Ability to learn quickly; Good communication and social skills

• Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
• Experience with data engineering and pipeline development
• Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification
• Knowledge of NLP techniques for text analysis and sentiment analysis
• Experience in analyzing time-series data for forecasting and trend analysis

• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills
• Strong presentation and public speaking skills.