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Job description
Real-time grid planning and operations at Pravah uses machine learning to lower blackout risk and volatility from extreme events for electric utilities.
A machine learning researcher shapes new modeling directions in GNNs, RL, or computer vision to serve grid applications and their physical constraints.
A power systems engineer bridges grid physics and the AI stack to ensure decisions reflect real-world physical fidelity.
A forward deployed engineer owns technical deployments end-to-end by understanding utility operations and translating them into implementation.
A founding engineer takes ownership of product deployment from design through rollout in production environments with high standards.
A weather scientist pushes AI-weather prediction frontiers to improve grid resilience and forecasting accuracy for operational needs.
A GTM or BD specialist builds commercial motion by navigating the utility landscape and shaping go-to-market strategy with clear strategic thinking.
High agency and bias for action drive building, fixing, and shipping from Day 1 with full ownership when facing ambiguity.
Strategic thinking aligns long-term roadmap with short-term execution to accomplish 10x progress for the modern grid decision engine.
Roles are proposed by candidates who define a point of view, identify a gap at Pravah, and fill it with their unique contribution to the mission.
Easy to work with partners balance friendliness and intensity while managing crazy, accelerating demands in the best way possible for the team.
Clear sense of personal strengths, identified gaps, and proposed solutions guide how each contributor fits into Pravah's mission and impact.
You gain access to hard open-ended problems, early shaping of technical direction, and close collaboration with a deeply technical founding team through direct effort.
About the role
The role centers on building foundational intelligence for the electric grid using machine learning. The team, rooted in AI and physical infrastructure, helps utilities make real-time decisions to cut blackout risk and volatility. The position suits candidates who define their own contributions and thrive in ambiguous, high-stakes problems.
Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.
Key facts
What you'll do
- Shape strategic thinking so long-term roadmaps and short-term execution align to drive 10x progress.
- Propose roles by defining a point of view, identifying gaps at Pravah, and filling them with unique contributions.
- Push AI-weather prediction frontiers to improve grid resilience and forecasting accuracy.
- Build commercial motion by navigating the utility landscape and shaping go-to-market strategy.
- Translate utility operations into technical implementation as a forward deployed engineer.
- Ensure physical fidelity in decisions as a power systems engineer bridging grid physics and the AI stack.
- Own product deployment from design through rollout as a founding engineer.
Requirements
- High agency and bias for action, building, fixing, and shipping from Day 1.
- Full ownership from Day 1, thriving in ambiguity and reasoning from first principles.
- High standards for building the core decision engine for the modern grid.
- Easy collaboration with relaxed yet intense partners who are hustlers.
- Strategic thinking to hold long-term roadmap and short-term execution together.
- A clear sense of personal strengths, identified gaps, and how you fill them.
Nice to have
- Background in power systems, weather science, machine learning research, business development, or operations.
- Experience defining technical direction and driving execution in early stage settings.
Skills & tools
- Machine learning for grid planning and operations.
- Tools for AI-physical infrastructure integration.
Practical notes
- The team is small and operates with high intensity.
- Remote work arrangements may apply; Good to know
About the company
Pravah is building foundational intelligence for the electric grid. We apply modern machine learning to complex physical infrastructure problems spanning grid operations, weather, and geospatial systems.