Engineering Jobs and Recruitment Solutions
AI and Machine Learning Jobs That Move Beyond the Hype
Artificial intelligence has crossed the line from experiment to infrastructure. Models now sit inside clinical systems, financial platforms, logistics engines and customer products. When they fail, the impact is real.
MRJ works with engineering teams building production-grade AI, not slide decks and prototypes. We recruit machine learning engineers, applied AI engineers and platform specialists who know how to move models from notebooks into reliable systems that can be monitored, governed and trusted.
If you’re looking for AI jobs or machine learning roles where the data is meaningful, the problems are complex and the engineering standards are high, this is where those conversations start.
The Future of AI and Machine Learning Jobs
The Gap Between Ambition and Reality
Everyone wants to be “AI-first”. Far fewer teams are ready to operate AI responsibly at scale.
Job specs promise ownership and impact, but often hide messy data foundations, fragile pipelines and unclear accountability once models hit production. Titles blur together. Expectations drift mid-process. Engineers are asked to move fast without the guardrails that make speed sustainable.
Common friction we see:
- Roles labelled “ML Engineer” that are actually analytics-heavy or experimental
- Production accountability without tooling, monitoring or governance
- Tool-driven hiring instead of problem-driven engineering
- Pressure to ship AI without clarity on risk, bias or compliance
At the same time, organisations are realising that AI success depends less on clever models and more on engineering discipline. Data quality, platform maturity, security, observability and ethical controls now matter just as much as accuracy.
This tension is what makes AI hiring difficult and what makes getting it right so valuable.
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AI and Machine Learning Jobs We Fill
AI careers are shaped by the systems you own and the decisions you’re trusted to make, not just the models you train.
We recruit across the full lifecycle of intelligent systems, from experimentation through to platform maturity and leadership.
Applied AI and Machine Learning
- Machine Learning Engineer
- Applied AI Engineer
- Data Scientist
- Research Engineer
- NLP and Computer Vision Engineer
Platforms, MLOps and Reliability
- MLOps Engineer
- AI Platform Engineer
- ML Infrastructure Engineer
- Model Reliability Engineer
- Cloud ML Engineer
Data Foundations and Intelligence
- Analytics Engineer
- Data Platform Engineer
- Feature Engineering Specialist
- Data Governance Lead
Leadership and Strategy
- Principal Machine Learning Engineer
- Head of AI
- AI Architect
- Responsible AI Lead
- Machine Learning Manager
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FAQ's
What AI and machine learning roles do MRJ recruit for?
We recruit across applied machine learning, data science, MLOps, platform engineering and AI leadership roles.
Can MRJ help us define what type of AI engineer we actually need?
Yes. We help you assess data maturity, platform readiness and delivery goals to avoid misaligned hires.
How do MRJ ensure technical quality in shortlists?
We screen for real production experience, system ownership and engineering depth, not just tool exposure.
Do MRJ support senior and leadership AI hiring?
Absolutely. We regularly place principal engineers, heads of AI and technical leaders.
Can MRJ help me find an AI role that fits my engineering style and values?
Yes. We focus on role clarity, engineering culture and long-term development.
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Ready to take your next step in AI and machine learning?
Submit your CV and our team will get in touch to explore roles that match your skills, your approach and where you want your career to go.