Machine Learning Operations Engineer

• 5+ years of hands-on experience in production ML infrastructure engineering, with a track record of deploying and operating AI models at scale
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Deep proficiency with Kubernetes and Docker for deploying and managing AI workloads across diverse environments
• Hands-on experience with CI/CD pipelines designed for AI and ML model lifecycle management
• Strong working knowledge of Nvidia Triton Inference Server and TensorRT
• Experience designing and managing infrastructure across multiple cloud platforms, including at least two of: GCP, AWS, Azure, CoreWeave
• Solid understanding of GPU cluster management and the performance tradeoffs across hardware configurations
• Experience with on-premise AI deployment and the infrastructure complexity it introduces
• Strong grasp of MLOps principles and AI model lifecycle management from experimentation through production
• Ability to work autonomously, make infrastructure decisions with limited oversight, and communicate technical tradeoffs clearly to senior leadership

• 7+ years of ML infrastructure experience, with increasing ownership of complex, multi-environment deployments
• Experience with Nvidia Fleet Command for managing distributed inference deployments
• Familiarity with GPU scaling research across hardware architectures beyond Nvidia
• Background working directly with research or data science teams to productionize experimental models
• Experience in high-growth startups or early-stage companies where infrastructure ownership is broad and fast-moving
• Familiarity with real-time performance monitoring and observability tooling for AI systems
• Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

If you're passionate about building the infrastructure that powers private, continuously-learning AI for the world's most demanding enterprises, we'd love for you to apply and help shape the foundation that makes custom AI a reality at scale.

• Base salary range: $130,000 - $200,000 annually
• Competitive equity package in venture-backed startup
• Performance-based bonus structure
• Annual merit-based salary reviews
• Stock

• Comprehensive medical, dental, and vision coverage (80% employer-paid)
• 401(k) plan with company match
• Unlimited PTO policy with 15 days minimum
• 11 paid company holidays

• Annual training and certification budget
• Access to online learning platforms
• Conference attendance opportunities
• Regular internal technical workshops and knowledge sharing sessions

• Onsite at Dallas HQ
• High-performance workstations
• Modern office space in Dallas with standing desks and ergonomics equipment
• Monthly team events and learning sessions
• Collaborative in-office environment fostering innovation and teamwork

We like to be efficient but do our due diligence.

Here’s what you’ll expect from us:

• Interview with Recruiter (30-60 minutes)
• Interview with Hiring Manager (30 minutes)
• Technical Interviews and/or Presentation (half to full day)
• Interview with CEO (30 minutes)

Hit that apply button:

• Detailed Resume
• Git Hub profile or code samples
• Portfolio of relevant work
• Brief cover letter describing your development experience

4MindsAI is an equal opportunity employer.

We value diversity and are committed to creating an inclusive environment for all employees.

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