Join Medifast: Transforming Lives with Healthy Habits

At Medifast, we are passionate about our mission of driving Lifelong Transformation, One Healthy Habit at a Time®. When you join us, you become part of a dynamic, fast-growing community dedicated to promoting health and wellness. If you want a rewarding career that makes a tangible impact on people's lives daily, Medifast could be the ideal place for you.

Machine Learning Engineer Position Overview

We are seeking a talented Machine Learning Engineer to join our team. The ideal candidate will have a strong background in machine learning, data analysis, and software engineering. This role involves developing and deploying scalable machine learning models to enhance our product offerings and improve the experiences of both Coaches and Clients.

Key Responsibilities

• Design, develop, and deploy machine learning models and algorithms to solve complex business problems in the health and wellness domain.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate machine learning solutions into production systems.
• Conduct thorough data analysis and feature engineering to support model development.
• Implement best practices for model training, validation, and evaluation.
• Monitor and maintain the performance of deployed models, ensuring they remain accurate and effective over time.
• Develop and maintain documentation for machine learning processes and models.
• Stay current with the latest advancements in machine learning and artificial intelligence to improve existing models and processes.
• Participate in code reviews and contribute to the development of team standards and practices.
• Work with large-scale datasets and distributed computing frameworks.
• Ensure compliance with data privacy and security regulations.

Role Scope

The Machine Learning Engineer will play a critical role in enhancing OPTAVIA’s capabilities through advanced machine learning techniques. While the position does not include direct reports, it involves extensive collaboration with cross-functional teams, supporting departments like product development, marketing, and finance. This role demands high technical expertise and problem-solving skills due to the complexity and scale of the data involved.

Qualifications and Skills

• Bachelor's degree in computer science, data science, machine learning, statistics, or a related field. A master's degree or PhD is preferred.
• Proficiency in programming languages such as Python, R, or Java.
• Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with big data tools and platforms (e.g., Hadoop, Spark, AWS, Google Cloud, Azure).
• Excellent problem-solving skills and critical-thinking ability.
• Effective communication skills to explain complex technical concepts to non-technical stakeholders.
• Ability to work collaboratively in a team and manage multiple projects simultaneously.
• Knowledge of software engineering principles, including version control, testing, and CI/CD.
• Understanding of data privacy and security principles.
• 4+ years of experience in machine learning or a related field.
• Proven track record of developing and deploying machine learning models in a production environment.
• Experience with large datasets and distributed computing environments.
• Preferred: Familiarity with artificial intelligence, neural networks, and demand forecasting models.

Why Medifast?

At Medifast, relationships are at the heart of everything we do. We believe in elevating our connections with one another and with our Coaches & Clients. Our core values – integrity, courage, teaming, accountability, empowerment, partnership, and diversity – are more than just words; they are celebrated and embodied in our daily actions.

We Lead By

• Mastering Relationships: Building trust, promoting collaboration, and being reliable.
• Innovating: Continuously improving, testing, refining, and expanding within our business strategy.
• Simplifying: Making processes measurable, repeatable, and scalable to focus on outcomes.
• Anticipating: Predicting long-term needs, challenging assumptions, and preparing for the unexpected.