Qualis Flow (Qflow)
Senior Machine Learning Engineer

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Who are we?
Qflow was founded in 2018 with a bold mission to empower the world to build responsibly. Our platform helps construction and development teams cut waste and reduce carbon emissions through real-time, data-driven insights.
We’ve built a cutting-edge platform that gives project teams real-time insights into materials, waste, cost, carbon, and quality right at the source. Using AI, machine learning, and smart integrations, our tech makes sense of chaotic data streams by extracting information from messy receipts and documents, auditing it against project requirements, flagging risks instantly, and feeding insights directly into reporting workflows. Our mobile app makes it effortless for workers on the ground to capture data in seconds — turning construction sites into real-time, data-rich ecosystems.
The impact? Less waste. Lower carbon. Smarter decisions. A construction industry that uses only what it needs — building a future that works for people and the planet.
We’re backed by leading climate-tech and construction-tech investors, including Systemiq Capital, Greensoil PropTech Ventures, and Suffolk Technologies, and have raised £11.2M in Series A funding to accelerate our international growth.
You should apply if...
You’re a Data Scientist or Machine Learning Engineer who wants to use your skills for impact, helping make one of the world’s most polluting industries more efficient, sustainable, and data-driven.
You enjoy solving complex, messy data challenges, turning raw information into reliable insights and AI-powered features that deliver measurable results. You’re curious, collaborative, and want to work in a place where your work directly contributes to how construction companies reduce waste, carbon, and cost at scale.
Your team and your role
We’re looking for a Data Scientist & ML Engineer to join our Data Experience Team. This team is at the intersection of data science prototyping and production-grade backend systems, which designs, develops, and deploys scalable, data-driven solutions powering Qflow’s platform.
Reporting to our Senior Engineering Manager, and working closely with our Tech Lead, you’ll you’ll balance innovation and delivery, researching and shaping early ML and AI prototypes into robust, production-ready features that take our product to the next level. Here’s what you’ll do day to day:
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
- Research, prototype, and productionise AI/ML solutions that deliver real business impact.
- Collaborate with Product and other engineers to identify opportunities and translate them into robust, data-driven solutions.
- Perform exploratory data analysis (EDA) to identify patterns, validate assumptions, and define model approaches.
- Build, train, and deploy predictive models and algorithms for use cases such as forecasting, optimisation, segmentation, and classification.
- Turn models into services, integrating them into APIs, pipelines, and Qflow’s wider system architecture.
- Maintain high standards in code quality, testing, documentation, and reproducibility.
- Contribute to data governance practices, including versioning, lineage, and validation.
- Share knowledge, mentor peers, and help embed a culture of data-driven thinking and continuous improvement across the team.
Our tech stack
The Data Experience Team works with Python and SQL for data processing, Azure and Terraform for cloud infrastructure, and modern ML/AI tools such as OpenAI and Gemini. We’re continuously raising our engineering standards through robust testing, CI/CD, and shared code quality practices. We value curiosity and innovation, always exploring new technologies to stay ahead of the curve.
Your skills
We’re looking for someone comfortable turning data into real impact, someone who brings together data science and the craft of software engineering to build reliable, scalable systems that make a difference. You might have started in one and grown into the other; what matters most is your ability to turn models and ideas into robust, production-grade features that deliver measurable results.
- 5+ years of experience in either a data-science or ML focused role or software engineering-focused environment, ideally with overlap.
- Advanced proficiency in Python and experience with some key ML frameworks (scikit-learn, PyTorch, TensorFlow).
- Experience taking ML models and/or backend systems from development through to production deployment.
- Solid SQL skills and familiarity with NoSQL data stores.
- Working knowledge of cloud architectures, distributed systems, and APIs (Azure preferred, but AWS or GCP are valuable).
- Familiarity with LLMs, prompt engineering, NLP, or image processing, and an ability to quickly learn new AI technologies (e.g., RAG pipelines).
- Exposure to CI/CD, infrastructure-as-code tools like Terraform, and containerisation with Docker or similar.
- Excellent communication skills, able to explain complex concepts to technical and non-technical audiences.
- Collaborative mindset, comfortable mentoring others and improving team capability.
- Comfort with ambiguity, prioritisation, and delivering incrementally in a startup environment.


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Our offer
- 🏡 Remote-first team
- 🇬🇧 Bi-weekly engineering team gatherings and wide-company gatherings once a quarter in our London HQ
- 🚝 Work travel expenses covered by Qflow
- 🏝️ 25 days annual leave + 3 days company closure at Christmas + bank holidays
- 🤒 Paid sick leave
- 🩺 Private medical insurance
- 🏥 Critical illness and life insurance
- 💰 Pension contribution up to 7%
- 👥 Enhanced family policy
- 🙋 Paid volunteering days
- ✈️ We allow our employees to work abroad for up to 90 days
- 🌎 We’ll offset your annual carbon footprint on your behalf via Ecologi
- 📚 Learning & development and career progression opportunities
- 🤩 Company social events (online and in person!)
- 💻 Company laptop and tools
Our promise
Creating an environment where everyone feels valued, respected and heard is at the forefront of everything we do. We are committed to providing equal employment opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status.
We created a culture that extends to all aspects of our operations, including step-free access, as we believe that everyone should have equal opportunities to access our facilities, services, and digital platforms.
Important Notice: No Recruitment Agencies
We kindly request that recruitment agencies refrain from contacting us regarding this job posting. We are solely interested in direct applications from candidates. Any unsolicited communication or resumes received from agencies will not be considered or acknowledged. We encourage candidates to apply directly through the provided application process. Thank you for your understanding.
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