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Mobileye Hr

To build exceptional teams that create cutting-edge vision technology by powering the autonomous future of mobility

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To build exceptional teams that create cutting-edge vision technology by powering the autonomous future of mobility

Strengths

  • EXPERTISE: World-class AI computer vision talent pipeline
  • PARTNERSHIPS: Strategic OEM relationships across global markets
  • CULTURE: Innovation-driven environment attracting top talent
  • LEADERSHIP: Strong executive bench with domain expertise
  • REPUTATION: Industry leader in ADAS employee value proposition

Weaknesses

  • RETENTION: Increasing attrition in key AI engineering roles
  • SCALING: Slow hiring processes hampering growth objectives
  • DIVERSITY: Underrepresentation in technical leadership positions
  • COMPENSATION: Below-market AI researcher compensation packages
  • TRAINING: Inadequate upskilling programs for emerging tech

Opportunities

  • REMOTE: Expand global talent acquisition through remote work
  • UNIVERSITY: Strengthen specialized AI academic partnerships
  • RESKILLING: Develop internal mobility program for legacy teams
  • AUTOMATION: Implement AI-powered talent acquisition system
  • CULTURE: Build differentiated employer brand in autonomy space

Threats

  • COMPETITION: Aggressive recruiting from tech giants for AI talent
  • BURNOUT: Increasing workload affecting employee wellbeing
  • REGULATIONS: Evolving compliance burdens stretching HR capacity
  • PERCEPTION: Public skepticism about AV safety affecting brand
  • ECONOMIC: Market volatility impacting compensation strategies

Key Priorities

  • TALENT: Implement AI talent retention strategy and compensation
  • DIVERSITY: Accelerate diverse technical leadership pipeline
  • AGILITY: Streamline hiring processes for critical AI positions
  • CULTURE: Reinforce safety-first innovation culture and brand
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To build exceptional teams that create cutting-edge vision technology by powering the autonomous future of mobility

RETAIN BRILLIANCE

Build world's best AI talent retention ecosystem

  • COMPENSATION: Implement AI talent market compensation adjustment for top 150 critical roles by June 30
  • EXPERIENCE: Launch AI researcher experience program with 90% satisfaction target by Q3
  • ANALYTICS: Deploy retention prediction model achieving 85% accuracy for critical talent by August
  • DEVELOPMENT: Create specialized career paths for 100% of technical leadership roles by September
DIVERSE INNOVATION

Accelerate inclusive technical leadership pipeline

  • REPRESENTATION: Increase women in technical leadership roles from 24% to 32% by Q4
  • DEVELOPMENT: Launch accelerated leadership program with 50 diverse high-potentials by July
  • SOURCING: Implement specialized diversity sourcing strategy reaching 40% diverse candidate slate
  • MENTORSHIP: Establish technical mentorship program pairing 100 mentor-mentee relationships
SPEED TO TALENT

Reimagine hiring process for world-class agility

  • EFFICIENCY: Reduce time-to-hire for specialized AI roles from 62 to 38 days by August
  • AUTOMATION: Deploy AI-powered candidate screening reducing recruiter admin time by 35%
  • EXPERIENCE: Achieve 90% positive candidate experience score across all technical hires
  • CONVERSION: Increase offer acceptance rate from 76% to 88% for AI engineering roles
SAFETY CULTURE

Embed safety-first innovation ethos across organization

  • MINDSET: Achieve 95% employee understanding of safety-innovation connection via pulse survey
  • RECOGNITION: Implement quarterly innovation awards with 25% focused on safety enhancements
  • DEVELOPMENT: Train 100% of managers on fostering psychological safety by end of Q3
  • BRANDING: Launch employer brand campaign generating 45% increase in qualified AI applicants
METRICS
  • RETENTION: 92% talent retention rate for critical AI roles
  • DIVERSITY: 32% women in technical leadership positions
  • SPEED: 38 days average time-to-hire for specialized roles
VALUES
  • Innovation First
  • Safety Above All
  • Excellence in Execution
  • Collaborative Problem Solving
  • Diversity & Inclusion
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Align the learnings

Mobileye Hr Retrospective

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To build exceptional teams that create cutting-edge vision technology by powering the autonomous future of mobility

What Went Well

  • TALENT: Successful hiring of specialized computer vision research team
  • DEVELOPMENT: Launch of new AI skills certification program with 87% uptake
  • ENGAGEMENT: Highest employee engagement scores in three years at 82%
  • PARTNERSHIPS: Successful university research talent pipeline established

Not So Well

  • RETENTION: 18% attrition in senior AI engineering roles, above target
  • DIVERSITY: Only 24% of technical leadership roles filled by women
  • COMPENSATION: Increasing compensation variance with market benchmarks
  • ACQUISITION: Time-to-hire for specialized roles exceeded targets by 31%

Learnings

  • COMPETITION: Need for specialized AI talent retention strategies
  • DEVELOPMENT: Internal mobility programs showing strong ROI for retention
  • CULTURE: Remote work flexibility directly correlates with engagement
  • ANALYTICS: Predictive attrition models need refinement for accuracy

Action Items

  • COMPENSATION: Implement targeted retention packages for critical AI roles
  • PROCESS: Redesign technical hiring process to reduce time-to-fill by 40%
  • DIVERSITY: Launch technical leadership development program for women
  • ANALYTICS: Deploy real-time talent dashboard for executive team by Q3
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To build exceptional teams that create cutting-edge vision technology by powering the autonomous future of mobility

Strengths

  • EXPERTISE: Deep AI talent bench driving internal HR innovation
  • TECHNOLOGY: Proprietary AI recruiting tools reducing time-to-hire
  • ANALYTICS: Advanced workforce analytics identifying talent trends
  • LEARNING: AI-powered personalized learning platform adoption
  • EXPERIENCE: Data-driven employee experience measurement system

Weaknesses

  • INTEGRATION: Siloed HR technologies limiting AI implementation
  • SKILLS: Limited data science capabilities within HR function
  • GOVERNANCE: Unclear AI ethics framework for HR applications
  • ADOPTION: Uneven manager utilization of AI-powered HR tools
  • LEGACY: Outdated HRIS limiting advanced analytics capabilities

Opportunities

  • PREDICTION: Implement AI-driven retention prediction models
  • MATCHING: Deploy skill-based talent marketplace platform
  • AUTOMATION: Scale intelligent workflow automation for HR tasks
  • INSIGHTS: Develop real-time talent intelligence dashboard
  • PERSONALIZATION: Create AI-powered career development paths

Threats

  • PRIVACY: Increasing data protection regulations limiting AI use
  • BIAS: Risk of algorithmic bias in AI-powered HR decisions
  • ACCEPTANCE: Employee resistance to AI-driven HR processes
  • COMPETITION: Competitors leveraging more advanced HR AI tools
  • EXPERTISE: Difficulty attracting AI specialists to HR function

Key Priorities

  • PREDICTION: Implement AI retention prediction for critical roles
  • GOVERNANCE: Develop comprehensive AI ethics framework for HR
  • CAPABILITIES: Upskill HR team on data science fundamentals
  • INTEGRATION: Create unified HR data platform for AI applications