Machine Learning Engineer
Apply NowCompany: iFIT, Inc.
Location: Logan, UT 84321
Description:
SUMMARY
iFIT's vision is to create the world's most holistic health and fitness platform, integrating all elements of health - physical fitness, mental health, nutrition, and active recovery - into a seamless interactive experience. We develop proprietary software that learns and adjusts to the habits of each person as it delivers immersive content that guides them on their own individual fitness journey.
We are currently seeking an ambitious pace-setter to join our team as a Machine Learning Engineer in a remote role. You'll be part of our AI team, working in a modern TypeScript/Python tech stack and using AWS and Terraform to build and deploy production ML services. Our engineering culture emphasizes autonomy - you'll own your services end-to-end, from development through deployment via GitHub Actions pipelines.
ROLE COMMITMENTS
Build and maintain production-grade machine learning systems and AI models
Drive technical excellence in ML engineering practices and infrastructure
Collaborate effectively across teams to deliver integrated AI solutio
Contribute to our engineering culture of ownership and innovation
Stay current with ML/AI advances and evaluate their potential application
ESSENTIAL DUTIES AND RESPONSIBILITIES
Design, develop and deploy production recommendation systems and generative AI models
Own the full ML lifecycle including data preparation, model development, training infrastructure, and production deployment
Build robust, scalable ML services using modern cloud infrastructure (AWS) and IaC (Terraform)
Write clean, tested code in TypeScript and Python following engineering best practices
Collaborate with product teams to understand requirements and translate them into technical solutions
Contribute to ML platform infrastructure and tooling
Mentor other engineers on ML best practices
Participate in code reviews and technical design discussions
Monitor and maintain ML systems in production
Document technical decisions and system architectures
iFIT's vision is to create the world's most holistic health and fitness platform, integrating all elements of health - physical fitness, mental health, nutrition, and active recovery - into a seamless interactive experience. We develop proprietary software that learns and adjusts to the habits of each person as it delivers immersive content that guides them on their own individual fitness journey.
We are currently seeking an ambitious pace-setter to join our team as a Machine Learning Engineer in a remote role. You'll be part of our AI team, working in a modern TypeScript/Python tech stack and using AWS and Terraform to build and deploy production ML services. Our engineering culture emphasizes autonomy - you'll own your services end-to-end, from development through deployment via GitHub Actions pipelines.
ROLE COMMITMENTS
Build and maintain production-grade machine learning systems and AI models
Drive technical excellence in ML engineering practices and infrastructure
Collaborate effectively across teams to deliver integrated AI solutio
Contribute to our engineering culture of ownership and innovation
Stay current with ML/AI advances and evaluate their potential application
ESSENTIAL DUTIES AND RESPONSIBILITIES
Design, develop and deploy production recommendation systems and generative AI models
Own the full ML lifecycle including data preparation, model development, training infrastructure, and production deployment
Build robust, scalable ML services using modern cloud infrastructure (AWS) and IaC (Terraform)
Write clean, tested code in TypeScript and Python following engineering best practices
Collaborate with product teams to understand requirements and translate them into technical solutions
Contribute to ML platform infrastructure and tooling
Mentor other engineers on ML best practices
Participate in code reviews and technical design discussions
Monitor and maintain ML systems in production
Document technical decisions and system architectures
- Education and Basic Qualifications
- 3+ years of experience building and deploying ML models in production
environments - Strong software engineering skills with TypeScript and Python
- Experience with recommendation systems and generative AI models
- Proven track record deploying ML services in AWS
- Expertise in ML frameworks like PyTorch or TensorFlow
- Authorized to work in the United States without sponsorship
- Experience with infrastructure as code (e.g., Terraform) and CI/CD pipelines
- 3+ years of experience building and deploying ML models in production
- Preferred Qualifications
- Experience with RAG systems and LLM fine-tuning
- Familiarity with the fitness/health domain
- Knowledge of ML monitoring and observability practices
- Open source contributions or technical blog posts
- MS/PhD in Computer Science, Machine Learning or a related field