Jobs at Gigaton

Lead and scale a high-performing software engineering organization building real-time AI control and optimization systems for heavy industrial plants. Responsibilities include coaching engineers and engineering managers, strengthening software quality and delivery practices, aligning engineering plans with company priorities, supporting machine learning and research teams, making technical trade-offs, and developing future technical leaders. The role requires continued technical involvement in architecture, debugging, design reviews, and pairing within a complex, safety-critical environment.

Works directly with the CEO across sales, marketing, hiring, fundraising, partnerships, customer preparation, industry expansion, and strategic initiatives. The role requires exceptional ownership, communication, analytical thinking, automation skills, and comfort operating in ambiguity. Responsibilities range from highly administrative execution to strategic problem-solving, with an emphasis on proactively identifying, completing, automating, or deprioritizing work that drives company impact.

Lead production of high-impact content across channels, build and run a repeatable content engine and calendar, own distribution strategy, collaborate with Sales/Product/Engineering, uphold brand voice and editorial standards, use AI tools to scale output, and support sales with case studies and technical proof points while growing into strategic ownership.

Open talent pool invitation: Gigaton seeks exceptional candidates across engineering, machine learning, product, commercial, and operations. Submit an application describing your background; the team will review and contact potential matches. Offers equity, flexible working, 30 days holiday, and a pension.

Lead deployments of AI-driven process control in heavy industry: integrate Gigaton AI into live plants, collaborate with operators and engineers, analyse plant data, design APC/MPC/PID-based control strategies, validate performance, and support scalable deployment playbooks while travelling to sites for commissioning and optimisation.

Lead architecture, deployment, and operation of secure, scalable cloud platform components across multi-cloud environments. Mentor engineers, design CI/CD and deployment patterns, work with customer cloud accounts to meet security constraints, and drive platform and DevEx improvements for ML and data workloads.

Build, test and deploy machine learning models and infrastructure for industrial control systems. Collaborate with product teams on customer projects, design scalable ML systems, establish engineering best practices, and develop tooling to support continuous testing and deployment in production industrial plants.