Release Manager (AI Models)

Location: London, United Kingdom; hybrid role based in the London office, with focused remote work and core hours. Relocation support and visa sponsorship are available where applicable.

Company

hirify.global develops an embodied AI platform for autonomous driving that enables vehicles to learn from real-world experience and supports scalable deployment across OEM partners.

What you will do

• Own the AI model release cycle and maintain a predictable release cadence while adapting to changing priorities.
• Coordinate ML engineering, evaluation and data science, software platform, testing, and product teams to resolve dependencies and keep releases moving.
• Run promotion gates from hypothesis through training, evaluation, validation, and deployment, defining what is ready to ship.
• Investigate regressions and integration issues, coordinate rollback or roll-forward decisions, and follow up on technical debt and corrective actions.
• Communicate release status, risks, and timelines to engineers and leadership, and lead post-release reviews.
• Build release frameworks, dashboards, KPIs, and automated tooling that improve release efficiency, developer experience, and deployment reliability.

Requirements

• 5+ years of experience in release management, software engineering, or a related field.
• Understanding of the SDLC and release management practices, including testing strategy, system integration, branching, and versioning.
• Conceptual understanding of ML fundamentals, including training data, training versus inference, model versions and checkpoints, and probabilistic model validation.
• Experience with CI/CD pipelines and automation tools such as GitHub, Buildkite, and CLI tools.
• Experience managing releases in complex, fast-moving systems and adapting processes and tooling as requirements, architecture, and timelines change.
• Strong problem-solving and decision-making skills when release trade-offs depend on limited or ambiguous data.
• Clear communication with engineers and leadership about priorities, risks, and decisions.
• Pragmatic, methodical, system-minded approach with strong release-engineering instincts and willingness to develop judgment for ML systems.

Nice to have

• Experience in AI/ML, autonomous vehicles, or robotics.
• Familiarity with MLOps methodologies and tooling.
• Experience with ML evaluation practices and tooling for physical systems, including simulation, model leaderboards, A/B testing, and shadow-mode testing.
• Awareness of model hardware and software dependencies.
• BSc or equivalent in Computer Science, Engineering, or a related technical discipline.

Culture & Benefits

• Hybrid working with in-person collaboration, remote work, core hours, and hands-on work in vehicle workshops and labs.
• Market-benchmarked salaries, meaningful equity, and comprehensive benefits.
• Health insurance, dental coverage, enhanced maternity and paternity leave, retirement or pension support where applicable, therapy access, wellbeing partnerships, and team socials.
• Learning and development budgets supporting training, conferences, and professional growth.
• Inclusive, fair, and respectful culture with meaningful ownership in a developing organizational environment.

Hiring process

• Initial 30-minute recruiter call.
• Competency interviews covering release management and cross-functional collaboration, followed by technical interviews with an assessment and case study.
• Final interview focused on mission and values alignment.