Software, Technical Program Manager

Osmo•Elizabeth, NJ

1d•$201,000 - $231,000•Onsite

About The Position

Osmo is a digital olfaction company focused on integrating a sense of smell into computers to enhance human health and well-being. The company is seeking a Software, Technical Program Manager to join its Software and AI organization. This role will act as a liaison between ML engineers, applied ML scientists, and software engineers, driving the development process, managing dependencies, and removing obstacles to facilitate team progress. The position requires technical credibility with engineers and ML scientists, including comfort with code reviews, code reading, and understanding model architecture decisions and their implications. The TPM will be responsible for driving technical execution and cross-functional delivery within a challenging applied AI environment.

Requirements

10+ years of combined experience in software engineering, ML engineering, or applied ML, plus a program management, technical program management, or engineering leadership role.
Demonstrated understanding of the ML development lifecycle (data, training, evaluation, validation, and deployment) and efficient ML system shipping.
Strong software fluency, including the ability to read code in at least one mainstream language, follow model architecture discussions, and understand system integration points.
Direct experience driving technical execution within a software or ML organization, successfully delivering complex, multi-team engineering projects from requirements to production.
Fluency with modern AI tools (LLMs, automation platforms, workflow builders) and a track record of using AI in project management.
Strong judgment under ambiguity, with the ability to establish milestones and produce clarity in undefined project spaces.
Clear, confident communication skills to bridge technical ML/engineering teams with business and scientific stakeholders.
Comfort pushing back on stakeholders, including senior leaders, regarding timelines, scopes, or resources.
Bachelor's degree or higher in computer science, a related STEM field, or equivalent engineering experience.
Authorized to work in the US and available on-site at the Elizabeth, NJ location.

Nice To Haves

Started as a software engineer or ML engineer and moved into program management, with continued occasional coding.
Hands-on experience orchestrating the delivery of applied ML products, ML platforms, generative AI systems, or scientific computing software.
Experience in a small, fast-moving AI or ML company where the engineering delivery process had to be built.
Comfort with Python, SQL, or notebooks for validating data or system status.
A track record of building AI-powered tools or workflows that significantly improved engineering organization operations.
Experience partnering with founders or senior technical leaders as a trusted execution partner.
A track record of operating successfully in a flat organization with strong individual contributor tracks, driving alignment and delivery without formal authority.

Responsibilities

Partner directly with software and ML leadership on execution strategy, resource planning, and timeline delivery.
Translate product and scientific ambitions into actionable engineering milestones and build the operational roadmap from architecture to deployment.
Build and utilize AI-powered tools and workflows for progress tracking, dependency mapping, stakeholder communication, and operational efficiency.
Own execution and dependency management, identifying and resolving cross-functional blockers between ML, software, and hardware teams, and making timeline tradeoffs visible.
Structure release readiness and deployment schedules for ML models and software systems, ensuring data availability for confident shipping.
Engage closely with engineering and ML work, participating in design reviews and reviewing code to understand system functionality.
Develop deep technical intuition about Osmo's AI systems, including architectural bottlenecks, latency risks, integration challenges, and ML lifecycle best practices.
Translate execution status, technical risks, and timeline shifts between technical ML teams and business, product, and scientific stakeholders, making complex tradeoffs understandable.
Bring structure to ambiguous technical initiatives by scoping, sequencing, and driving progress without unnecessary process.
Surface blockers, technical risks, and capacity limits early with proposed solutions and contingency plans.
Help define and establish best practices for technical program management at Osmo.