Spait Infotech
AI/ML Engineer

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Key Requirements
- Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or a related field.
- Strong knowledge of Python.
- Understanding of Machine Learning algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, and Clustering.
- Basic knowledge of Deep Learning and neural networks.
- Familiarity with NumPy, Pandas, Scikit-learn, and Matplotlib/Seaborn.
- Basic understanding of TensorFlow or PyTorch.
- Knowledge of statistics, probability, and data preprocessing.
- Understanding of SQL and databases.
- Familiarity with Git/GitHub.
- Good problem-solving and analytical skills.
- Academic projects, internships, or certifications in AI/ML are an advantage.
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.
Start with a chat, not a search bar
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.
Key Responsibilities


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- Assist in developing and testing machine learning models.
- Collect, clean, preprocess, and analyze datasets.
- Perform feature engineering and exploratory data analysis.
- Train, evaluate, and improve ML models.
- Implement basic deep learning models under guidance.
- Develop Python scripts and notebooks for data processing and model development.
- Evaluate model performance using appropriate metrics.
- Assist in deploying ML models into applications or APIs.
- Monitor model performance and troubleshoot issues.
- Work with senior engineers and data scientists on AI/ML projects.
- Maintain documentation for datasets, models, experiments, and results.
- Stay updated with emerging AI/ML technologies and tools.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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