ML Infrastructure Engineer at Gridmatic

Cupertino, California, United States

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Energy, AI & Machine Learning, DataIndustries

Requirements

3+ years of experience as an engineer
Deep understanding of codebases and ability to write readable, scalable code
Experience researching and implementing deep learning models
Experience in distributed training and inference of large models on GPU clusters, utilizing PyTorch, PyTorch Lightning, and Ray
Comfortable with large-scale data storage infrastructure and formats (e.g., Zarr, SQL, feature stores)
Strong sense of independence and ownership
Mission-driven and enthusiastic about working toward a renewable grid and the intersection of ML and energy
Strong deep learning fundamentals
Strong software engineering skills

Responsibilities

Own a significant piece of the ML platform while building and iterating scalable, robust distributed infrastructure for ML training, inference, and evaluation on large-scale time-series and weather datasets
Optimize throughput and cost by supporting model training and deployment across multiple clusters and clouds
Improve the efficiency of machine learning models and other workloads by optimizing latency, throughput, and memory consumption
Help define the long-term vision for Gridmatic’s ML platform
Play a key role in mentoring junior engineers and interns

Skills

Machine Learning

Distributed Systems

GPU-based Training

Scalable Infrastructure

High-Performance Computing

Deep Learning

Software Engineering

Time-Series Data

Weather Data

Gridmatic

AI-driven optimization for renewable energy assets

About Gridmatic

Gridmatic uses artificial intelligence to improve the performance and profitability of renewable energy assets. It serves renewable energy generators by predicting energy prices and managing risks, while helping storage operators optimize revenue and minimize non-performance risks. For consumers, Gridmatic aims to lower energy costs and support renewable energy procurement. The company stands out by combining advanced algorithms with market expertise to modernize energy markets and contribute to decarbonization.

Cupertino, CaliforniaHeadquarters

2020Year Founded

$5.8MTotal Funding

EARLY_VCCompany Stage

Energy, AI & Machine LearningIndustries

11-50Employees

Benefits

Hybrid Work Options

Flexible Work Hours

Risks

Increased competition from AI-driven energy optimization companies may erode market share.

Regulatory changes in Texas could impact operations as a Retail Electric Provider.

Cybersecurity threats to AI systems pose risks to data integrity and reliability.

Differentiation

Gridmatic uses AI to optimize renewable energy asset performance and profitability.

The company offers tolling, offtake, and supply contracts for clean energy assets.

Gridmatic is a licensed Retail Electric Provider in Texas, enhancing market credibility.

Upsides

Increased interest in AI-driven energy solutions boosts partnerships with energy providers.

The Inflation Reduction Act offers tax incentives, enhancing Gridmatic's financial attractiveness.

Advancements in battery technology improve storage efficiency, aligning with Gridmatic's focus.

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