Pythian
AI/ML Engineer

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Why You
As an AI / ML Engineer, you will be a contributor to the design, development, and implementation of Artificial Intelligence and Machine Learning solutions. Your primary focus will be on developing, implementing, and maintaining robust, scalable, and reliable AI/ML pipelines, with an emphasis on integrating and optimizing models, including Large Language Models (LLMs) and Generative AI technologies, into client and internal products. Your role requires a deep knowledge of ML engineering best practices and the AI ecosystem, coordinating with data scientists and software engineering teams.
If this is you, and you wonder what it would be like to work at Pythian, reach out to us and find out!
Intrigued to see what a life is like at Pythian? Check out #pythianlife on LinkedIn and follow @loveyourdata on Instagram!
Not the right job for you? Check out what other great jobs Pythian has open around the world! [Pythian Careers](Pythian Careers)
What You Will Be Doing
- Develop, deploy, and maintain robust AI and machine learning pipelines for internal and client-driven projects.
- Deploy, manage, and scale AI models, including pre-trained models (e.g., LLMs) and custom ML models, into production environments.
- Work with data scientists to implement model prototypes into scalable, production-ready AI systems.
- Optimize and tune model performance, latency, and cost-efficiency on cloud platforms.
- Integrate AI/ML solutions with major cloud platforms (AWS, GCP, Azure) and utilize containerization technologies (Docker, Kubernetes) for consistent deployment.
- Apply standard MLOps practices, including continuous integration/continuous delivery (CI/CD), model versioning, monitoring, and maintenance systems.
- Coordinate with software engineering teams to ensure seamless integration of AI capabilities into applications and user workflows.
- Stay up to date with advancements in AI/ML technologies, Generative AI, and MLOps deployment strategies.
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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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
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.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What We Need From You
- Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field.
- 4 to 5 years of progressive experience in machine learning engineering, software development with an ML/AI focus, or a related role.
- 1-3 years experience with ADK or other agentic frameworks.
- Strong programming skills in Python and proficiency in ML/AI frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Hands-on experience in deploying and working with pre-trained models, such as Large Language Models (LLMs) or similar Generative AI technologies, into production environments.
- Solid experience with cloud platforms (AWS, GCP, Azure) and container orchestration using Docker and Kubernetes.
- In-depth knowledge of Data Engineering principles, ETL/ELT processes, and version control systems (e.g., Git).
- Experience in orchestrating Machine Learning pipelines using open-source tools like Kubeflow or managed cloud services.
- Experience in building and optimizing scalable AI/ML systems.
- Familiarity with MLOps best practices, including model monitoring, logging, and CI/CD pipelines for AI assets.
- Strong communication and teamwork skills, with an ability to work effectively across cross-functional teams including solution architects and data scientists.
What You Will Receive
- Love your career: Competitive total rewards package. Blog during work hours; take a day off and volunteer for your favorite charity.
- Love your work/life balance: Flexibly work remotely from your home, there’s no daily travel requirement to an office! All you need is a stable internet connection.
- Love your coworkers: Collaborate with some of the best and brightest in the industry!
- Love your development: Hone your skills or learn new ones with our substantial training allowance; participate in professional development days, attend training, become certified, whatever you like!
- Love your workspace: We give you all the equipment you need to work from home including a laptop with your choice of OS, and an annual budget to personalize your work environment!
- Love yourself: Pythian cares about the health and well-being of our team. You will have an annual wellness budget to make yourself a priority (use it on gym memberships, massages, fitness and more). Additionally, you will receive a generous amount of paid vacation and sick days, as well as a day off to volunteer for your favorite charity.


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Hiring Disclaimer
The successful applicant will need to fulfill the requirements necessary to obtain a background check. Accommodations are available upon request for candidates taking part in any aspect of the selection process.
AI Disclaimer
Pythian may utilize Enterprise Generative Artificial Intelligence (AI) tools or features throughout its hiring process. These tools help us manage high volumes of applications efficiently and may be employed to review applications, analyze resumes, and assist with other recruitment steps. While Pythian uses AI in its hiring process, it does not substitute for human judgment. Our Talent Acquisition Team reviews all AI-generated recommendations, and the system is subject to regular bias audits to ensure fairness and compliance with all applicable employment and human rights laws. All final hiring decisions are made by, and remain the responsibility of, human decision-makers. By applying for this position, you consent to Pythian’s use of these AI tools in the evaluation of your application. You have the right to request a human review of any solely AI-driven decision or to request an accommodation. Should you require further details regarding the processing of your data, please reach out to us.
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