Software Engineer, Machine Learning

About Granica

Granica is pioneering data optimization for large scale AI and analytics. Our unified platform slashes storage and compute costs while turbo charging data pipelines, empowering enterprises to turn petabytes of raw data into actionable intelligence. Backed by $45 M from NEA and Bain Capital Ventures, we’re scaling fast at the intersection of AI research, distributed systems, and go to market.

The Team

We’re hiring Software Engineers to join our Machine Learning team, which works at the heart of Granica’s platform. This team partners closely with research, product, and platform engineering to productionize new ML algorithms, optimize platform performance through ML techniques, and fine-tune models for specific customer needs. You’ll also contribute to building and improving internal training, evaluation, and deployment pipelines.

The Role

You’ll help translate research into real-world impact — designing and implementing machine learning systems that drive product features and platform efficiency. You’ll work across the ML lifecycle, from experiment design and training to deployment and monitoring, with an emphasis on production-quality engineering and measurable outcomes.

What You’ll Do

Invent

Explore ML-driven solutions to increase the compression, performance, and accuracy of Granica’s platform.

Research and prototype novel approaches to pattern detection, feature modeling, and automated optimization.

Develop internal experimentation and evaluation frameworks to accelerate model iteration and analysis.

Own

Productionize ML models for real-time and batch inference in high-throughput environments.

Fine-tune models to meet customer-specific performance objectives and compliance constraints.

Design and maintain training and inference pipelines, with built-in traceability, versioning, and monitoring.

Learn & Collaborate

Work closely with Research, Platform, and Product Engineering teams to bring ML innovation to production.

Engage with customer-facing teams to understand real-world data characteristics and evolving needs.

Drive continuous improvements in model performance, scalability, and deployment efficiency.

What You Bring

4+ years of experience in ML engineering or applied machine learning roles.

Strong coding skills in Python and experience with ML frameworks like PyTorch, TensorFlow, or JAX.

Experience with model serving and MLOps tools: TorchServe, TensorFlow Serving, FastAPI, MLflow, or similar.

Familiarity with data pipeline tools like Apache Airflow, Spark, Kafka, or Ray.

Experience building CI/CD pipelines and production systems for ML workflows.

Familiarity with observability stacks (e.g., Prometheus, Grafana, ELK) for monitoring model and system behavior.

Bonus: Background in data compression, representation learning, or distributed inference is a plus.

Compensation

$180,000 – $220,000 (base) plus meaningful equity. Uncapped accelerators for over achievement.

Benefits

Generous 401(k) with company match

Premium health, dental, and vision coverage for you and your dependents

Unlimited PTO plus company wide recharge weeks

Catered lunch & dinner at our offices

Immigration sponsorship and support

Company hackathons and off sites

Equal Opportunity

Granica celebrates diversity and is committed to creating an inclusive environment for all employees.