TurbineOne

Business Development Rep

• Develop the business strategy. Find the relevant military Requirement that our technology is uniquely capable of serving. Map the engagement and education pathways with relevant stakeholders, reduce the risk of employment through exercises/prototypes, and then secure funding for the capability.
• Deliver new revenue. Partner, directly and contractually, with the U.S. Navy to include special operations and Marine Corps units.
• You will identify sales opportunities, drive leads into the sales funnel by directly engaging buyers, pitch our product (with support from the Ops team), document the scope of work (in collaboration with the CTO), and negotiate the contract (with pricing approval from the CEO).
• Identify the right military leaders with the right kind of power, then with the utmost care and ethical conduct, convince that person to become a fanatical champion for TurbineOne’s product.
• Document warfighter needs in a manner that is explainable to Silicon Valley engineers and investors.
• Contribute to the company's overall business strategy and marketing positioning.
• Educate the U.S. military on how AI/ML can advance their missions in frontline environments.

Principal, Business Development – Undersea Warfare

Content Manager

• Develop and execute TurbineOne’s content strategy to expand brand visibility and audience engagement.
• Collaborate closely with the Sales Enablement and Growth teams to ensure content directly supports go-to-market initiatives, proposal efforts, and customer engagement.
• Own and manage TurbineOne’s podcast—from guest coordination and recording to editing, publishing, and promotion across channels.
• Manage the editorial and social media calendar across blogs, newsletters, events, podcasts, and thought leadership.
• Craft and refine TurbineOne’s voice and tone for target audiences, from defense and government stakeholders to industry partners and the general public.
• Produce, edit, and direct high-quality multimedia content—especially video and motion graphics—that tell our story with clarity and impact.
• Partner with internal teams to showcase impactful customer use cases, readiness exercises, and product milestones.
• Track performance analytics to optimize distribution, reach, and conversion through SEO, AEO, and emerging channels.
• Streamline the content pipeline through efficient workflows, tools, and AI-driven processes.
• Explore innovative content formats and platforms to expand engagement and thought leadership presence.

Machine Learning Engineer

• Deliver edge-focused product experiences, integrating the latest in machine learning, to support the missions of intelligence officers, frontline soldiers and security forces around the world.
• Work closely with our expert design team to develop novel and intuitive user experiences allowing laypeople to take full advantage of machine learning as a tool.
• Knowing the limits and shortcomings of machine learning, design systems and application flows that, nonetheless, allow machine learning to be a force multiplier for our frontline warfighters.
• Collaborate with the infrastructure team, and other product teams, to create an efficient and elegant application stack, taking into account the resource constraints of the edge-focused environments we deploy into.
• Work with ML engineers to design and build our internal modeling APIs, making sure they support optimal user experiences on the front end.

Machine Learning Product Engineer

Sales

• Lead TurbineOne’s Foreign Military Sales strategy—from identifying allied demand signals to structuring and executing FMS and DCS (Direct Commercial Sales) pathways.
• Engage directly with U.S. and partner-nation defense organizations, including DSCA, SAF/IA, USASAC, NAVSUP, and key foreign procurement offices.
• Shape go-to-market strategy for coalition partners, coordinating with internal engineering, legal, and operations teams to align exportable configurations and licensing.
• Stay current on international economic and military trends to enable go-to-market strategy.
• Develop and manage country-specific opportunity pipelines—from initial engagement through Letter of Request (LOR), LOA, and case implementation.
• Support program capture and execution, including proposal development, pricing, contract negotiation, and delivery oversight.
• Advise leadership on export compliance, ITAR considerations, and risk management related to international technology transfer.
• Build strategic partnerships with primes, integrators, and in-country representatives to accelerate fielding and sustainment.
• Represent TurbineOne at international defense events and with embassies, attachés, and foreign MOD delegations.
• Collaborate with the CEO to define and execute a multi-year international growth plan that expands our allied customer base.

Director of Foreign Military Sales

Financial Planning and Analysis

• Develop and lead TurbineOne’s overall financial strategy, including annual planning, capital allocation, and scenario modeling.
• Act as a strategic partner to the CEO and leadership team on corporate development, pricing, product strategy, and organizational growth.
• Oversee day-to-day financial operations—including budgeting, forecasting, reporting, compliance, and cash management—with a focus on discipline and scalability.
• Develop financial products for conversations with investors and board-level stakeholders.
• Create financial models that drive future business operations (e.g. Based on the probable revenue, how many people do we need to hire and by when?) Lead the FP&A work.
• Support diligence on potential acquisitions or strategic partnerships.
• Ensure financial systems, tools, and reporting processes are robust, auditable, and ready to support Department of Defense (DoD) and federal compliance standards.
• Manage the various financial service providers including bookkeeping, tax, and banking.

Head of Finance

Full-stack Engineer

• Deliver on capabilities for TurbineOne’s autonomous vehicle focused efforts; build simulation infrastructure to model behavior.
• Be a generalist in the uncrewed vehicle space while having opportunities to specialize.
• Collaborate with Design and Product Management on feature design, delivery schedule and trade off decision points.
• Act as a product owner—shape the direction of T1’s code and features.
• Report directly to the Product Engineering Manager.
• Support a number of vehicle platforms across architectures and AI accelerators; work within a Vue 3 client, Golang server, and MongoDB storage layer.

Senior Software Engineer – Simulation

Data Scientist

• Ingesting, organizing, and maintaining large-scale training datasets from open-source resources and contract-specific artifacts
• Creating and managing data cataloging systems to ensure datasets are findable, accessible, and ready for ML training pipelines
• Designing and implementing data labeling workflows, including managing external labeling vendors and quality assurance processes
• Building and maintaining YOLO-style manifests and annotation formats for custom computer vision datasets
• Performing data cleaning, validation, and augmentation to ensure high-quality training data
• Conducting exploratory data analysis and generating insights about dataset characteristics, biases, and coverage gaps
• Supporting the ML research team with statistical analysis, experiment design, and model evaluation
• Developing data pipelines and automation tools for continuous data ingestion and processing
• Collaborating with ML engineers to optimize data loading and preprocessing for training efficiency
• Process incoming datasets from various sources, performing quality checks and organizing them into our data management system
• Create or review annotation schemas and coordinate with labeling teams to ensure consistent, high-quality labels
• Write Python scripts to clean, transform, and validate datasets for specific ML training requirements
• Analyze dataset statistics and create visualizations to identify potential issues or opportunities for improvement
• Collaborate with the ML research lead to design experiments and evaluate model performance across different data splits
• Document dataset characteristics, versioning, and lineage to maintain reproducibility and compliance