MLOps Engineer
Description For MLOps Engineer
Motive is a pioneering company that serves over 120,000 customers, from Fortune 500 enterprises to small businesses, providing innovative solutions for physical operations management. The platform uniquely combines safety, operations, and finance into a single system, enhanced by industry-leading AI capabilities.
As an MLOps Engineer at Motive, you'll be at the forefront of driving crucial infrastructure and platform initiatives related to AI/ML pipelines. This role offers an exciting opportunity to work on highly efficient and scalable model Training & Inference systems, while also contributing to the development of tools, automation, and CI/CD systems.
The position requires a strong technical background with at least 3 years of experience in designing and implementing scalable software systems. You'll be working with cutting-edge technologies including Kubernetes, Docker, and various cloud platforms, while collaborating with cross-functional teams to deliver robust AI solutions.
What makes this role particularly appealing is the combination of technical challenges and leadership opportunities. You'll not only be building sophisticated MLOps infrastructure but also mentoring junior team members and implementing best practices. The position offers the flexibility of remote work while being part of a company that's making a significant impact across multiple industries including transportation, logistics, construction, and energy.
Join Motive to be part of a diverse and inclusive workplace where you can make a real difference in revolutionizing physical operations through technology. The role offers an excellent opportunity to work with advanced AI/ML technologies while contributing to a product that makes operations safer, more productive, and more profitable for businesses across the globe.
Responsibilities For MLOps Engineer
- Design, develop and deploy MLOps infrastructure for AI and deep learning models
- Develop scalable cloud AI/ML pipelines for customer-facing inference services
- Implement MLOps practices for model development automation and deployment
- Address availability issues and scale pipelines while maintaining SLAs
- Collaborate with cross-functional teams on end-to-end product features
- Mentor junior team members
Requirements For MLOps Engineer
- Bachelor's Degree in Computer Science, Electrical Engineering, or related field
- 3+ years experience in designing and operating scalable software systems
- Hands-on experience with MLOps and DevOps tools
- Solid CS foundations in data structures, algorithms and software engineering
- Excellent verbal and written communication skills
- Knowledge of computer vision, deep learning, or machine learning is a plus
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