Data and AI
Hire data engineers, data scientists and AI engineers
Every company rolling out AI learns the same thing in month two: the AI is only as good as its data. Data engineers build the pipelines, data scientists and ML engineers make the models useful and safe, and AI engineers build the tools people actually use. BLS projects data scientist jobs to grow 35% by 2035, and postings with AI or machine learning in the title are about three times what they were in May 2024.
How the job changed
| Role | Then | Now |
|---|---|---|
| Data analyst | Built the monthly dashboard | Uses AI to find answers, then checks whether they're true |
| Data engineer | Ran nightly batch jobs | Builds the clean, governed data every AI tool depends on |
| Data scientist | Shipped one model a quarter | Evaluates, tunes and monitors models already in use |
| ML / AI engineer | A job at tech giants | Builds AI features and agents on company data, at banks, plants and hospitals |
Roles we place
- Data engineers (Databricks, Snowflake, Spark, Azure Data Factory)
- Data scientists
- Machine learning engineers and MLOps
- AI engineers
- Analytics and BI developers (Power BI, Tableau)
- Data architects
Typical pay
| Role | Pay | Source |
|---|---|---|
| Data engineer | Median posted salary about $155,000 | Axial Search, 2026 |
| Data scientist | Median $120,230 a year | BLS |
| Machine learning engineer | $124,250 to $177,000 | Robert Half 2027 Salary Guide |
| AI engineer | $154,500 to $196,750 | Robert Half 2027 Salary Guide |
National figures. Pay varies by location and seniority; a Role Review gives you the number for your market.
Contract or hire?
Contract the migration or the first build. Hire the person who will own it after.
How we find them
We don't post jobs. We map who is doing this work today, reach out with a message written for each person, and draw on a database we've built since 2007. A recruiter screens every candidate and verifies identity and work history before you see them. Most roles are filled in one to three weeks.
Sources: BLS Occupational Outlook: data scientists, CompTIA, Oct 2026.
Questions
Data scientist or data engineer first?
Engineer, almost always. Models fail on bad data, not bad math.
Do we need an ML engineer to use AI?
Not to use off-the-shelf tools. You do once you're building AI on your own data or putting it in front of customers.
Can you find people who've done this outside tech?
Yes. We look for people who have built data and AI systems at banks, plants and health systems, not only at software companies.