AI Engineer - Data Science

AI overview

Design and deploy bespoke AI solutions for top-tier enterprises, delivering high-impact products that empower users and solve complex business challenges.

causaLens delivers Digital Workers that enterprises can truly rely on. Soon, competing without Digital Workers will be impossible. Just as it became unthinkable to manufacture without machines. We’ve built the first factory and Operating System for creating, deploying, and governing Digital Workers. For too long, enterprises have been bogged down by repetitive work, an overload of tools, and costly consultancies.


It’s time to simplify.


It’s time for Digital Workers to take on the repetitive workflows, freeing humans to focus on what matters most. Trusted by leading companies like J&J, Cisco, IPG Group, and Syneos Health.


Backed by over $50M in funding from world-class investors, including Molten Ventures (formerly Draper Esprit), Dorilton Capital, and IQ Capital, plus visionary angel investors such as the CEO of Revolut.



Here are 2 articles that define our culture:
1.
A Hiring Framework for a New Kind of Services Company

2. The Primacy of Winning

Requirements

We are seeking AI Engineers with strong data science expertise who are passionate about helping world-leading enterprises put cutting-edge AI agents into production. You’ll work on impactful, high-visibility projects - designing, building, and delivering intelligent solutions that solve real business problems at scale.

What you’ll bring:

  • experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.)

  • critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows.

  • Client-facing experience with a forward-deployed engineering mindset. You’ll work directly with both technical teams and business stakeholders to understand real-world challenges and deliver solutions that drive measurable impact.

  • Strong solution architecture and delivery skills: ability to translate complex business problems into scalable, intelligent AI solutions.

    What you’ll do:

  • Collaborate directly with top-tier enterprises to understand needs, design and deploy bespoke agentic workflows.

  • Design and implement robust architectures that leverage the latest AI technologies.

  • Lead the delivery of high-impact AI products from concept to deployment.

You’ll collaborate with top-tier enterprises to design and deploy bespoke data science agents, empowering users to fully leverage the capabilities of our platform.

Benefits


We care about our people’s lives, both inside and outside of causaLens. Beyond the core benefits like competitive remuneration and a good work-life balance, we offer the following:

  • 25 days of paid holiday, plus bank holidays

  • carry over/sell holiday options (up to 5 days)

  • Share options

  • Pension scheme

  • Happy hours and team outings

  • Referral bonus program

  • Cycle to work scheme

  • Friendly tech purchases

  • Benefits to choose from, including Health/Dental Insurance

  • Special Discounts

  • Learning and development budget

  • Work abroad days

  • Office snacks and drinks

Logistics

Our interview process consists of screening sessions with the hiring manager and a "Day 0" which involves an approx 3 hours in-person challenge followed by an in-person presentation and interviews. 

Have questions? We encourage open dialogue—reach out anytime.

If you require accommodations during the application process or in your role at causaLens, please contact us at [email protected]

Perks & Benefits Extracted with AI

  • Flexible Work Hours: Happy hours and team outings
  • Free Meals & Snacks: Office snacks and drinks
  • Health Insurance: Benefits to choose from, including Health/Dental Insurance
  • Learning Budget: Learning and development budget
  • Other Benefit: Work abroad days
  • Paid Time Off: 25 days of paid holiday, plus bank holidays

global_economy.predict().optimize() CausaLens leads #CausalAI and #TimeSeries research

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