Software, Technical Program Manager
Osmo
| Company | Osmo |
| Category | Engineering |
| Location | Elizabeth |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 23 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
Who we are at Osmo:
Osmo is a digital olfaction company, on a mission to give computers a sense of smell to improve the health and wellbeing of human life. Why? Our sense of smell both enriches and saves lives, and has a deep and direct connection to our emotions and memory.
Olfactory Intelligence has applications across industries including fragrance, manufacturing, security, medicine, and more. We believe in the power of automation and thoughtfully applied AI/ML to solve problems beyond the reach of human intuition alone. Osmo is headquartered in Elizabeth, NJ, with an additional office in Somerville, MA.
THE ROLE
We're hiring a Software, Technical Program Manager to embed directly with Osmo's Software and AI organization. You'll be the connective tissue between our ML engineers, applied ML scientists, software engineers, and the rest of the company — driving how and when we build, managing complex dependencies, and removing blockers so the team can move.
This is a software-specific TPM role, and we mean it. You'll need to be technically credible with engineers and ML scientists at a detailed level — comfortable in a design review, comfortable reading code, comfortable understanding a model architecture decision and its downstream impacts. You'll be driving technical execution and cross-functional delivery inside one of the most ambitious applied AI problems in the world.
WHAT YOU'LL DO
- Partner directly with software and ML leadership as their primary thought partner on execution strategy, resource planning, and timeline delivery.
- Translate Osmo's product and scientific ambitions into clear, actionable engineering milestones. Build the operational roadmap to get us from architecture to deployment.
- Build and use AI-powered tools and workflows in your own work — for progress tracking, dependency mapping, stakeholder communication, and operational efficiency.
- Own execution and dependency management. Identify cross-functional blockers between ML, software, and hardware teams, make timeline tradeoffs visible, and drive them to resolution.
- Structure release readiness and deployment schedules for ML models and software systems. Bring the right data forward so the team can ship with confidence.
- Sit close to the engineering and ML work. Be in design reviews. Read the code when you need to. Understand how the system actually works, not just what's on the Gantt chart.
- Develop deep technical intuition about Osmo's AI systems — understanding architectural bottlenecks, latency risks, integration challenges, and what a healthy ML lifecycle looks like.
- Translate execution status, technical risks, and timeline shifts between deeply technical ML teams and business, product, and scientific stakeholders. Make complex tradeoffs legible to non-engineers without losing the substance.
- Bring structure to ambiguous technical initiatives — scope them, sequence them, and keep them moving without adding process for its own sake.
- Surface blockers, technical risks, and capacity limits early — with proposed solutions and contingency plans, not just escalations.
- Help define what good looks like for technical program management at Osmo, and set the bar for those who follow.
QUALIFICATIONS
- 10+ years of combined experience in software engineering, ML engineering, or applied ML, plus a program management, technical program management, or engineering leadership role. We want both: engineering depth and operational execution instinct.
- Demonstrated understanding of the ML development lifecycle — data, training, evaluation, validation, and deployment — and a real point of view on how to efficiently ship ML systems.
- Strong software fluency. You can read code in at least one mainstream language, follow a model architecture discussion in real time, and understand system integration points in a design review.
- Direct experience driving technical execution inside a software or ML orga