Hayden AI — a technology pioneer harnessing computer vision to transform transit systems and government agencies — is hiring a Staff Deep Learning Engineer in a hybrid role accessible to UAE-based candidates. This is a senior, technical leadership position within Hayden’s Deep Learning team — responsible for leading end-to-end delivery of large-scope perception projects from design through production, defining technical approaches, mentoring engineers, and driving alignment across Deep Learning, Platform, and Product teams. With 8+ years of production ML experience required and a compensation package of $230,522–$299,679 plus equity and bonus, this is one of the most technically prestigious and financially exceptional deep learning engineering roles available to top-tier ML professionals in 2026.
About Hayden AI — Computer Vision for the Real World
Company: Hayden AI — Harnessing Computer Vision for Transit & Government Use-Cases
Mission: Accelerate transit, enhance street safety, and drive toward a sustainable urban future
Products: Mobile perception systems · Bus lane enforcement · Transportation optimization · Edge AI
Department: Research & Development — Perception Team (Deep Learning)
Infrastructure: Cloud ML models + on-device edge deployment serving diverse real-world use-cases
Why This Hayden AI Staff Deep Learning Role Is a Career-Defining Opportunity
Elite Technical Leadership: Staff-level engineering role at the crux of Hayden AI’s perception platform — your technical decisions shape the product
Exceptional Compensation: $230,522–$299,679 base salary plus equity and company-wide bonus — genuinely top-of-market for senior ML engineers
Real-World AI Impact: Your perception models operate in production — powering transit enforcement and safety systems that serve millions of urban commuters
Edge + Cloud Breadth: Rare opportunity to lead ML deployment across both cloud infrastructure and on-device edge systems simultaneously
Position Overview
This Staff Deep Learning Engineer position at Hayden AI is a senior technical leadership role at the absolute core of the company’s perception and deep learning capability. You will lead end-to-end delivery of large-scope perception projects — from initial design through model training, evaluation, optimization, and production deployment — while defining and documenting technical approaches, driving alignment across teams, mentoring junior and mid-level engineers, and shaping the team’s technical roadmap. Hayden AI’s Deep Learning team runs production models both in the cloud and on edge devices, and the MLOps infrastructure underpinning this deployment — pipelines, experiment tracking, and CI/CD for ML — is a core part of this role’s scope. This is a role for an exceptionally experienced ML engineer who brings both deep technical mastery of computer vision and perception systems and the technical leadership presence to influence cross-team architecture decisions and set engineering quality standards across the organization.
Why This Is the Deep Learning Engineering Career Opportunity of 2026: Staff Deep Learning Engineers with 8+ years of production ML experience, computer vision and perception expertise, edge deployment experience, and technical leadership credentials represent the rarest and most valuable engineering talent profile in the global AI industry. The combination of Hayden AI’s genuinely impactful mission — making transit systems safer and more efficient through AI — with a $230K+ base, equity, and bonus compensation package makes this one of the most complete and career-defining ML engineering opportunities available to senior AI professionals in 2026.
Key Responsibilities
Technical Leadership — Perception Project Delivery
- Lead end-to-end delivery of large-scope perception projects — from initial technical design and architecture definition through model development, evaluation, optimization, and full production deployment on cloud and edge infrastructure
- Define and document clear, rigorous technical approaches for perception system development — producing design documents and project plans that drive aligned understanding and execution across Deep Learning, Platform, and Product teams
- Drive cross-team technical alignment — influencing architecture decisions, resolving technical disagreements with evidence-based reasoning, and ensuring perception solutions are developed with the right tradeoffs between performance, scalability, and operational reliability
- Contribute to the team’s technical roadmap and help evaluate and prioritize new technical investments — bringing deep ML expertise and engineering judgment to roadmap decisions that shape the future of Hayden AI’s perception capability
Deep Learning Model Development & Production Deployment
- Design, develop, train, and evaluate advanced deep learning models for computer vision and perception use-cases — applying mastery across at least two perception verticals to build models that perform reliably in Hayden AI’s demanding production environments
- Optimize trained models for production deployment — applying quantization, pruning, distillation, and hardware-specific optimization techniques to meet the performance, latency, and memory requirements of both cloud and on-device edge deployments
- Lead the deployment of perception models to cloud infrastructure and edge devices — ensuring reliable, scalable, and maintainable production systems that serve diverse real-world transit and government use-cases at the scale Hayden AI’s customers require
- Apply working proficiency across the full ML lifecycle — model training, evaluation, optimization, cloud deployment, edge deployment, and MLOps — maintaining a broad technical foundation alongside deep expertise in core perception domains
MLOps, Infrastructure & Engineering Quality
- Work closely with the Platform team to build out Hayden AI’s MLOps infrastructure — developing and maintaining robust ML pipelines, experiment tracking systems, and CI/CD processes for ML that achieve better scale and operational reliability
- Set and uphold engineering quality standards across model development, MLOps tooling, and production deployment — conducting rigorous code reviews, defining quality gates, and establishing best practices that elevate the engineering standard of the entire team
- Design and implement ML CI/CD pipelines that automate model evaluation, validation, and deployment — reducing time-to-production for new perception models and ensuring that quality standards are consistently enforced at every stage of the ML delivery lifecycle
Engineering Mentorship & Team Development
- Mentor junior and mid-level deep learning engineers through structured code review, architecture design feedback, and hands-on technical pairing — helping them grow their technical depth, engineering judgment, and professional confidence
- Lead technical discussions and whiteboard sessions — creating a collaborative, intellectually rigorous engineering culture where the best technical ideas win on their merits regardless of seniority or organizational hierarchy
- Thrive in a fast-paced startup environment — bringing the organizational resilience, technical creativity, and bias-for-action mindset that enables Hayden AI to out-move and out-innovate larger, slower competitors
Qualifications & Requirements
Educational Requirements
- Bachelor’s degree in Computer Science, Robotics, Computer Vision, Electrical Engineering, or a closely related technical field — mandatory educational qualification for all applicants
Experience Requirements
- 8+ years of professional experience building and deploying ML models in production — this is a strict minimum requirement; prior experience in a tech lead or staff-equivalent engineering role is strongly preferred
- Mastery in at least 2 of Hayden AI’s 4 perception verticals — demonstrating depth of computer vision and perception engineering expertise that goes beyond generalist ML experience
- Demonstrated working proficiency across the full ML engineering lifecycle — model training, evaluation, optimization, cloud deployment, edge deployment, and MLOps including pipelines, experiment tracking, and CI/CD for ML
Leadership & Professional Skills
- Proven ability to mentor engineers at multiple levels, lead technical discussions, and influence cross-team architecture decisions — demonstrating staff-level engineering leadership that shapes organizational technical culture
- Excellent written and verbal communication skills — able to write clear, well-structured design documents, technical project plans, and engineering specifications that drive aligned execution across cross-functional teams
- Thrive in a fast-paced, ambiguous startup environment — comfortable with evolving priorities, rapid iteration cycles, and the organizational agility required to operate effectively at a growing AI company
About Hayden AI & Computer Vision in Urban Mobility
Hayden AI is at the forefront of applying computer vision and mobile perception technology to one of the most practically important and socially meaningful challenges in urban infrastructure — making public transit systems faster, safer, and more reliable for the millions of people who depend on them every day. From bus lane enforcement and bus stop compliance monitoring to broader transportation optimization and beyond, Hayden AI’s mobile perception systems deliver real-time AI-powered intelligence that empowers transit agencies and government clients to make evidence-based operational improvements at city scale. The company’s deep learning team sits at the absolute technical center of this mission — building and maintaining the advanced perception models that power every Hayden AI customer use-case, from cloud inference to on-device edge deployment. For Staff Deep Learning Engineers who want to apply elite ML expertise to real-world problems that genuinely matter — and be compensated at the very top of the market for doing so — Hayden AI represents one of the most compelling, purposeful, and financially exceptional engineering career opportunities available anywhere in the AI industry in 2026.
Your Career Growth Path: Staff Deep Learning Engineer → Principal Engineer → Distinguished Engineer → VP of Engineering / Head of AI Research — a technically elite, commercially impactful, and financially exceptional career trajectory at the intersection of computer vision, edge AI, and real-world urban mobility intelligence.
Who Should Apply?
- Staff / Senior ML Engineers: With 8+ years of production deep learning experience, computer vision or perception domain expertise, and a track record of technical leadership in engineering teams
- Computer Vision Specialists: With hands-on experience training, optimizing, and deploying perception models for real-world detection, classification, or tracking applications
- Edge AI Engineers: With experience deploying ML models to on-device edge platforms — balancing model performance, latency, and memory constraints for real-world embedded AI applications
- MLOps Leaders: With ML pipeline design, experiment tracking, and CI/CD for ML experience who want to operate at staff level across both model development and infrastructure domains
- Tech Lead Engineers: Who combine deep ML technical expertise with demonstrated ability to mentor engineers, lead architecture discussions, and influence product and platform roadmap decisions
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