Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead AI & Data Science

Dar
London
21 hours ago
Create job alert

Company Overview:


Interested in this role You can find all the relevant information in the description below.

Dar, the founding member of the Sidara group, is an international multidisciplinary consulting organization specializing in engineering, architecture, planning, environment, project management, facilities management, and economics. Sidara operates in 60 countries with 20,500 professionals, Dar connects people, places, and communities through innovative solutions to the world's most complex challenges. We deliver projects from inception through completion, embracing challenges to empower communities worldwide. Learn more at .

Our Vision and Values:

We aspire to be the chosen home of those with a gift for crafting solutions that empower people and an unwavering passion for learning and innovation. Our core values shape our culture and guide our decision-making. We are committed to:

  • Excellence
  • Responsibility
  • Empowerment
  • Connectivity
  • Courage

Role Overview

We are seeking a seasoned and visionary Lead, AI & Data Science to drive the strategy, development, and deployment of advanced AI solutions across our Digital Solutions department. This role is leadership and technically grounded, you will define and guide our AI roadmap, mentor a team of experts, and ensure delivery of world-class solutions. While you will not be coding daily, you must possess deep technical knowledge across the AI/ML spectrum and the ability to review, advise, and step in when critical decisions or mentorship are needed.

You will play a pivotal role in building and scaling the AI & Data Science team, shaping career paths, and representing the department in global events, partnerships, and thought leadership platforms.

Key Responsibilities

Strategic & Technical Leadership

  • Define and lead the AI & Data Science vision and roadmap , aligned with business priorities.
  • Provide technical oversight for AI initiatives across domains:
  • Generative AI & LLMs (fine-tuning, RAG pipelines, multi-agent systems).
  • Predictive Analytics & Time-Series Modeling .
  • Computer Vision & Multimodal AI .
  • Reinforcement Learning & Optimization .
  • Knowledge Engineering & Semantic Search .
  • Edge AI & Real-Time AI Deployments .
  • Act as the architect and reviewer of AI systems, ensuring scalability, robustness, and compliance.
  • Guide the adoption of MLOps best practices (CI/CD for ML, monitoring, retraining, governance).
  • Drive innovation while balancing pragmatism and production readiness .

Mentorship & Team Development

  • Build and grow a world-class AI & Data Science team , including hiring, onboarding, and performance management .
  • Mentor and coach team members to elevate technical depth and problem-solving skills.
  • Create career development plans, learning paths, and certification opportunities for the team.
  • Foster a culture of collaboration, experimentation, and continuous improvement .

Collaboration & Representation

  • Work closely with Product Managers, Solution Architects, and Engineering Leads to embed AI across the product suite.
  • Translate business challenges into scalable, impactful AI solutions .
  • Represent the department in industry conferences, technical forums, and client engagements .

Required Qualifications

  • Significant experience in AI/ML, including experience in a technical leadership or team lead role .
  • Strong knowledge (architectural & practical) of:
  • LLMs, RAG, and AI Agents .
  • Predictive analytics & time-series forecasting .
  • Computer vision, multimodal learning, and geospatial AI .
  • Reinforcement learning and optimization techniques .
  • MLOps practices & data pipelines .
  • Ability to review code, design architectures, and guide technical teams .
  • Advanced degree (Master’s or PhD is a plus) in Computer Science, AI, Data Science, or related technical field.

Preferred Qualifications

  • Experience with digital twins, IoT/OT data, and smart systems .
  • Familiarity with vector databases.
  • Knowledge of AI ethics, explainability, and regulatory compliance .
  • Experience representing organizations at global conferences and industry summits .

Career Development & Opportunities

  • Build and scale your own AI & Data Science team .
  • Define career plans and growth frameworks for your team members.
  • Access to continuous training, certifications, and skill development programs .
  • Opportunities to attend and present at global AI/tech events .
  • Collaborate with top-tier technology partners and thought leaders .

Related Jobs

View all jobs

Lead AI & Data Science...

Lead AI/ML Data Engineer

Data science: AI Reporting Lead

Data science: AI Reporting Lead

Head of AI - Data Science & Machine Learning

Head of AI, Data Science and Machine Learning

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.