We are seeking a skilled Machine Learning Operations (MLOps) Engineer to join our team. The ideal candidate will play a crucial role in bridging the gap between our software-development, data-management, and AI-modeling teams. This role will be responsible for ensuring seamless implementation of ML development processes, and deployment of machine learning models into production on our distributed / IoT devices. We are looking for candidates who are collaborative, adaptive and mission-driven. This is a remote position based in the United States. Candidates will be expected to collaborate cross-functionally with remote teams based across the country.
Responsibilities
- Work collaboratively with Cloud teams to design and build data infrastructure/pipelines to support ML model development workflows
- Develop and maintain MLOps infrastructure to automate model training, testing, deployment, monitoring, model provenance, and version control
- Collaborate with ML modelers, data scientists, and software developers to implement best practices in continuous integration, continuous deployment (CI/CD), and version control for data analytics and machine-learning systems
- Work with AI developers to design and build LLM workflows for fine-tuning, distillation, and system evaluation
- Foster a culture of open communication, innovation, and continual improvement
- 8+ years of professional experience including 5+ years of proven experience in data engineering architecture and implementation for ML workflows
- 3+ years of proven experience in MLOps, DevOps, or related field, with a strong understanding of machine-learning lifecycle-management
- Experience with data pipelines for ML workflows
- Experience with big data distributed processing such as SPARK, DASK, or RAY
- Experience with MLOps frameworks
- Proficiency in CI/CD tools, containerization technologies (Docker, Kubernetes), and cloud services (AWS, Azure, GCP)
- Excellent collaboration and communication skills to work effectively across teams
- Advanced degree in Computer Science, Engineering, or another related field
- Experience with data infrastructure and ML Ops for distributed / IoT systems
- Experience with LLM development workflows including training, deploying, and model management
- Experience with time-series datasets
- Experience with data science and algorithms development
Location: This position can be performed remotely from anywhere in the United States.
Our Commitments:
Utilidata values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws.
We are committed to:
- Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful
- Empowering employees to solve problems and work together to make a difference
- Providing mentorship and growth opportunities as part of a collaborative team
- A flexible work environment with flexible paid time off
- Competitive compensation and benefits, including health, dental, vision, and employer-match 401k
Top Skills
What We Do
Utilidata is an AI-powered technology company that is working with NVIDIA to create the next generation of AI-embedded infrastructure, starting with the electric grid. Karman, our distributed AI platform, operates on our custom NVIDIA module, makes data available for accelerated computing at the edge, and trains AI models locally.
Karman is embedded in grid devices - starting with smart meters - to transform the way utility companies operate. As the electric grid becomes more complex with the rapid increase of electric vehicles, distributed solar, batteries, heat pumps and extreme weather, utilities need real-time visibility of grid conditions and dynamic, software-defined infrastructure. Karman provides real-time visibility and AI at the grid edge so utilities can better utilize customer energy resources, reduce power outages, and enable quicker storm recovery.
We are a mission-driven, collaborative, and adaptive team working to do what’s right, even when it’s hard. With backgrounds in electric engineering, power systems engineering, software engineering, data science, and energy policy, we bring a unique perspective on the solutions the energy industry needs.
We are committed to ensuring a diverse, inclusive, and flexible workplace where employees are provided mentorship and growth opportunities and are empowered to solve problems as part of a collaborative team.
