Machine Learning Operations Engineer

Flippa.com; Providence (RI); Remote; USD 140,000 - 170,000; Full time

Job summary

An innovative energy technology company is seeking a skilled MLOps Engineer to bridge software development and AI modeling teams. In this remote role, you will design and build data infrastructure to support machine learning workflows, ensuring efficient deployment of models on distributed IoT devices. Join a mission-driven team that values collaboration and innovation, where your contributions will enhance the clean energy transition. This role offers a flexible work environment and competitive compensation, making it an exciting opportunity for professionals passionate about technology and sustainability.

Benefits

Flexible Paid Time Off

Health Insurance

Dental Insurance

Vision Insurance

Employer-Match 401k

Mentorship Opportunities

Collaborative Team Environment

Qualifications

• 8+ years of experience in data engineering and MLOps.
• Strong understanding of ML workflows and lifecycle management.
• Proficient in CI/CD tools and cloud services.

Responsibilities

• Design and build data infrastructure for ML model workflows.
• Develop MLOps infrastructure for model training and deployment.
• Collaborate with teams to implement CI/CD best practices.

Skills

MLOps

Data Engineering

Machine Learning Lifecycle Management

Collaboration

Communication

Education

Bachelor's Degree in Computer Science or related field

Advanced Degree in Computer Science or Engineering

Tools

Docker

Kubernetes

AWS

Azure

GCP

SPARK

DASK

RAY

Job description

Utilidata is a fast-growing energy technology company using distributed artificial intelligence (AI) to accelerate the clean energy transition and better serve utility customers. 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. Utilidata’s distributed AI platform, called Karman, is powered by our custom NVIDIA module and will transform the way utility companies operate with real-time visibility at the grid edge to better utilize customer energy resources, reduce power outages, and enable quicker storm recovery.

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.

Minimum Qualifications

• 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.

Enhanced Qualifications (Nice to Have)

• 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.

Salary Range:

$140,000 to $170,000 depending on experience.

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.