What an AI and machine learning engineer does
An AI and machine learning engineer builds, deploys and maintains models that make predictions or automate decisions inside your products and operations. The work includes preparing training data, selecting and training models, building services or APIs around them, integrating large language models where they fit and monitoring performance once a model is live. They work closely with data engineers, data scientists and software developers.
Many machine learning projects stall between a promising prototype and a working system. The gap is usually engineering: data pipelines, testing, deployment, monitoring and cost control. Finch screens candidates for models they have actually shipped, their Python and framework skills and how they handle data quality, privacy and model drift, so the engineers you meet can move your AI work from experiment to everyday use.
Typical responsibilities
- Prepare, label and validate training data with data engineering colleagues
- Train, evaluate and tune machine learning models for defined business problems
- Package models as services or APIs and deploy them to production
- Integrate large language models and retrieval tools where they suit the use case
- Monitor model accuracy, drift, latency and cost after release
- Document model behaviour, limitations and data sources
Qualifications and credentials
- A degree in computer science, engineering, statistics, mathematics or a related field; graduate degrees are common but not always required
- Strong Python skills and experience with frameworks such as PyTorch, TensorFlow or scikit-learn
- Experience with MLOps practices such as experiment tracking, model registries and containerized deployment
- Working knowledge of cloud machine learning services on AWS, Azure or Google Cloud
- Understanding of privacy, bias and responsible use of data in model design
Who hires an AI and machine learning engineer
- Banks, insurers and fintech firms
- SaaS and technology companies
- Retail and e-commerce businesses using recommendations or forecasting
- Health technology and life sciences companies
- Logistics and manufacturing firms applying predictive models
Where we recruit AI and machine learning engineer candidates
We fill AI and machine learning engineer roles for employers across Toronto and the GTA, including North York, Scarborough, Etobicoke, Vaughan, Markham, Richmond Hill, Mississauga, Brampton, Oakville, Burlington, Oshawa and Pickering, and for employers across Canada. GTA employers can meet us at our North York office by appointment.
What Finch checks before you meet a candidate
- Models the candidate has deployed to production, and how they were monitored
- Python, framework and cloud skills matched to your stack
- Approach to evaluation, testing and poor-quality data
- Awareness of privacy, bias and model limitations
- Ability to explain trade-offs to product owners and leadership
Interview questions to ask
- Tell me about a model you put into production. How did you know it was still working months later?
- When would you recommend a simple rules-based approach instead of machine learning?
- How would you evaluate whether a large language model is giving our users accurate answers?