- Be a key member of a growing team (data scientists, data engineers, DevOps engineers) that designs and implements predictive analytics solutions in a production environment, leveraging a variety of statistical models and machine learning algorithms
- Deploy machine learning models into production environments. Integrate machine learning algorithms with existing systems and application
- Design, build, and maintain the infrastructure for machine learning operations
- Collaborate with DevOps teams to ensure scalability, reliability, and security of ML systems
- Implement automation tools and processes for model training, testing, and deployment. Streamline and optimize the endtoend machine learning lifecycle
- Build tools and capabilities for model management and model performance monitoring
- Collaborate effectively with the team and across crossfunctional stakeholders
- Model a highperformance culture with critical thinking, problemsolving, learning, collaboration, and experimentation within the team
- Bachelor's degree completed in Computer Science or a related field
- 3+ years of experience with artificial intelligence, software engineering, MLOps, DevOps, or data engineering, in a professional role
- Experience with Azure DevOps, CI/CD, Terraform, Python and other scripting languages
- Experience with integrating DevSecOps practices and principles throughout the project life cycle
- Experience with Big Data technologies, cloudbased analytics, nonrelational datastores, data visualization tools, and opensource tools for data processing
- Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira or Azure DevOps.
- Travel required: Minimal (a couple of time a year)
- Experience with Databricks and Azure cloud platform, machine learning services, and best practices
- Experience in opensource AI/ML tools, frameworks technologies (for example, TensorFlow, PyTorch, scikitlearn, Apache MXnet, Spark MLlib, etc.)
- Experience with predictive analytics in Healthcare, Insurance or Consumer Credit industry
- Demonstrate integrity and ethics in daytoday tasks and decision making, adhere to FinThrive's core values of being customercentric, agile, reliable and engaged, operate effectively in the FinThrive environment and the environment of the work group, maintain a focus on selfdevelopment, and seek out continuous feedback and learning opportunities
- Support FinThrive's Compliance Program by adhering to policies and procedures pertaining to HIPAA, FDCPA, FCRA, and other laws applicable to FinThrive's business practices; this includes becoming familiar with FinThrive's Code of Ethics, attending training as required, notifying management or FinThrive's Helpline when there is a compliance concern or incident, HIPAAcompliant handling of patient information, and demonstrable awareness of confidentiality obligations
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Machine Learning Operations Engineer - Gurugram, India - FINTHRIVE INDIA PRIVATE LIMITED
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Description
Impact you will make :
Join a group of highly talented and motivated data scientists and data engineers with significant healthcare experience to help a thriving Healthcare function.
Build a highly functional and efficient Data Science & Machine Learning platform that brings together data from disparate sources and allow FinThrive to design and run complex algorithms to provide insights into the Healthcare business operations.
Partner with internal business, product, and technical teams to analyze requirements to deliver solutions to complex issues. Participate in development and oversee maintenance of code to ensure consistency, quality, best practices, and performance of applications.What you will do :