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Head of AI/ML - Job Opportunity at Equans

Greater London, GB
Full-time
Executive
Posted: June 7, 2025
On-site
£120,000 - £160,000 per year plus 10% bonus, reflecting the executive nature of this role in the London market where AI/ML leadership positions in large infrastructure companies command premium compensation due to the specialized combination of technical expertise and business transformation responsibilities required.

Benefits

Premium life insurance coverage at 3x annual salary providing exceptional financial security
Competitive 10% performance bonus significantly above industry standard
Flexible car or car allowance package enhancing personal mobility
Comprehensive private healthcare coverage ensuring priority medical access
Robust 5% pension contribution supporting long-term financial planning
Exclusive employee discount schemes across major retail brands
Subsidized gym membership promoting work-life balance
Tax-efficient cycle to work scheme supporting sustainable commuting
Flexible holiday purchase scheme allowing extended personal time
Corporate social responsibility days demonstrating company values commitment
Comprehensive professional development opportunities including qualifications funding
Lucrative employee referral rewards program
Inclusive employee networks providing career advancement support
24/7 employee assistance program with mental health app access

Key Responsibilities

Build and lead a high-performing AI/ML and data science team capable of delivering transformative business value across multiple divisions
Establish comprehensive knowledge sharing frameworks and professional development processes to maximize team effectiveness
Transform organizational data strategy through systematic improvements in collection, quality, and accessibility infrastructure
Drive rapid progression of AI/ML solutions from conceptual design to full-scale production deployment
Deploy high-impact AI/ML solutions across diverse business units with measurable technical performance and business value metrics
Deliver quantifiable improvements in operational efficiency, service quality, and cost reduction with documented ROI for each implementation
Collaborate across all Equans UK&I divisions to identify and implement AI/ML solutions addressing critical business challenges
Build strategic relationships and engagement at both C-suite executive and operational levels across the organization
Provide oversight and management of multiple concurrent AI/ML implementation projects at various development and deployment stages
Collaborate on UK AI/ML strategy development ensuring alignment with overall business strategy and coordination with individual operating units

Requirements

Education

Advanced degree (Masters or PhD) in Computer Science, Data Science, Artificial Intelligence, Engineering, or related technical field

Experience

Demonstrable experience leading successful AI/ML and data science projects from conception through to implementation, with measurable business impact and user adoption

Required Skills

Comprehensive knowledge of machine learning algorithms, neural network architectures, deep learning frameworks, and Large Language Models Proven ability to develop, train, and optimise models for production environments Strong foundation in statistics, feature engineering, and experimental design Ability to transform business problems into well-defined data science problems with appropriate evaluation metrics Expertise in designing robust deployment frameworks for machine learning models / large language models, monitoring solutions, and performance optimisation Experience establishing best practices, conducting code reviews, and mentoring others in AI/ML development Ability to evaluate emerging technologies and research for practical business applications Experience in developing, operationalising and commercialising data-driven products or solutions, particularly those leveraging AI/ML technologies
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Sauge AI Market Intelligence

Industry Trends

The infrastructure and energy services sector is experiencing unprecedented digital transformation driven by net-zero commitments and sustainability mandates, creating massive demand for AI/ML leaders who can operationalize data science across traditional industrial operations. Companies like Equans are racing to integrate predictive maintenance, energy optimization, and smart building technologies to maintain competitive advantage in the evolving green economy. Large Language Models and generative AI are revolutionizing how infrastructure companies approach documentation, compliance, and knowledge management, with early adopters seeing 30-40% efficiency gains in project planning and regulatory reporting processes. The convergence of IoT sensors, edge computing, and AI/ML in building management and energy systems is creating new revenue streams and service models, requiring leaders who can bridge traditional engineering expertise with cutting-edge data science capabilities.

Role Significance

Expected to build and manage a team of 15-25 data scientists, ML engineers, and AI specialists across multiple specialized functions, with additional oversight of cross-functional project teams involving hundreds of technical professionals across various business divisions.
This is a senior executive position reporting directly to C-suite level, with full P&L responsibility for AI/ML initiatives across a £17 billion revenue organization. The role holder will be instrumental in shaping the strategic direction of digital transformation across multiple business units, with significant influence on operational efficiency and competitive positioning.

Key Projects

Implementation of predictive maintenance AI systems across critical infrastructure assets reducing downtime by 25-40% Development of energy optimization algorithms for smart building management reducing operational costs by 15-30% Creation of automated compliance and documentation systems using Large Language Models Deployment of computer vision systems for safety monitoring and quality assurance in construction and maintenance operations Building AI-powered demand forecasting and resource allocation systems for optimal project delivery

Success Factors

Ability to translate complex AI/ML concepts into tangible business value propositions that resonate with both technical teams and executive stakeholders, ensuring sustained investment and organizational buy-in for transformation initiatives. Strong change management capabilities to navigate the cultural shift from traditional engineering approaches to data-driven decision making across a large, established organization with diverse operational units. Deep understanding of regulatory compliance and safety requirements in infrastructure and energy sectors, ensuring AI/ML solutions meet stringent industry standards while delivering innovation. Exceptional relationship building skills to establish trust and collaboration between technical teams, operational units, and executive leadership across multiple business divisions and geographic locations. Strategic vision to identify and prioritize high-impact use cases that demonstrate clear ROI while building organizational capabilities for future AI/ML initiatives.

Market Demand

Extremely high demand with limited qualified candidates, as the intersection of AI/ML expertise and infrastructure/energy sector knowledge represents a critical skills gap that most companies are struggling to fill in their digital transformation initiatives.

Important Skills

Critical Skills

Deep learning and neural network expertise is absolutely essential as infrastructure optimization requires sophisticated pattern recognition and predictive modeling capabilities that traditional statistical methods cannot achieve. The ability to design and implement custom architectures for specific industrial applications will be fundamental to success. Production deployment and MLOps capabilities are critical given the mission-critical nature of infrastructure systems where AI/ML failures can have significant safety and financial consequences. Experience with robust monitoring, failover systems, and performance optimization in production environments is non-negotiable. Business acumen and stakeholder management skills are vital for translating technical capabilities into business value and securing organizational buy-in for major transformation initiatives. The ability to communicate complex AI/ML concepts to non-technical executives and operational teams will determine the success of implementation efforts.

Beneficial Skills

Knowledge of IoT and edge computing architectures would be highly valuable given the distributed nature of infrastructure assets and the need for real-time AI/ML processing at remote locations with limited connectivity. Understanding of regulatory compliance frameworks in energy and infrastructure sectors would provide significant advantages in designing AI/ML solutions that meet industry-specific requirements and accelerate deployment timelines. Experience with sustainability metrics and ESG reporting would be increasingly valuable as companies face growing pressure to demonstrate environmental impact and progress toward net-zero commitments through quantifiable data-driven insights.

Unique Aspects

This role offers the rare opportunity to drive AI/ML transformation across the entire spectrum of infrastructure services, from smart buildings and green mobility to district energy and decentralized renewables, providing unprecedented scope for impact and innovation.
The combination of Bouygues' industrial heritage with cutting-edge AI/ML implementation creates a unique environment where traditional engineering excellence meets advanced data science, offering distinctive competitive advantages in the market.
Access to diverse, real-world datasets from critical infrastructure operations provides exceptional opportunities for developing and testing AI/ML solutions with immediate practical applications and measurable business impact.
The role's strategic importance to Equans' digital transformation agenda ensures high visibility with senior leadership and significant influence on company direction, making it an ideal platform for career advancement and industry recognition.

Career Growth

Typical progression to C-suite or equivalent strategic roles within 3-5 years, given the high-visibility nature of this position and the critical importance of AI/ML transformation in the infrastructure sector.

Potential Next Roles

Chief Technology Officer or Chief Digital Officer at major infrastructure or energy companies Head of Digital Transformation at multinational industrial conglomerates AI/ML leadership roles at technology consulting firms specializing in industrial applications Executive positions at AI/ML startups focused on infrastructure and energy solutions Senior advisory or board positions in companies undergoing digital transformation

Company Overview

Equans

Equans operates as a major subsidiary of Bouygues, one of France's largest industrial conglomerates, providing the role holder with access to substantial resources, international expertise, and strategic stability. The company's focus on energy transition and net-zero initiatives positions it at the forefront of the green economy transformation, offering significant opportunities for AI/ML innovation in sustainable infrastructure.

As a leading player in the £17 billion European energy services market with operations across 50+ countries, Equans holds a strong competitive position with established client relationships across government, public sector, and commercial segments, providing a robust platform for AI/ML solution deployment.
The UK & Ireland operation employs 13,500 professionals and serves as a strategic hub for the company's English-speaking markets, with this AI/ML leadership role positioned to influence not only local operations but potentially serve as a model for global AI/ML implementation across the broader Equans organization.
Large corporate environment with established processes and governance structures, balanced by strong commitment to innovation and digital transformation. The company's emphasis on diversity and inclusion, demonstrated through multiple employee networks and positive action initiatives, suggests a progressive culture that values different perspectives in driving technological advancement.
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