Data and ML engineers who turn raw data into dependable pipelines and models.
Analytics and machine learning depend on data that arrives on time and means what people think it means. Our data and ML engineers build the pipelines, warehouses and deployment paths that make that true.
- Matched to your stack and domain
- NDA and IP terms agreed upfront
- CMMI / ITIL-aligned delivery
- Individual, dedicated team or project-based
What our data & ml engineers work on
- Batch and streaming data pipelines with monitoring
- Data modelling for warehouses such as BigQuery and PostgreSQL
- Feature engineering and model training workflows
- Model deployment, versioning and drift monitoring
- Data quality checks and documentation of lineage
When it makes sense to add this role
- Reports disagree because data is inconsistent across systems
- A model prototype needs a production path
- You are building a warehouse or analytics platform
- An AI project needs reliable data foundations
Skills and tools
How to engage data & ml engineers through RFsoftLab
- 1
Share requirements
Tell us the role, stack, seniority and start date. A short call or the form below is enough.
- 2
Receive matched profiles
We propose people whose experience fits your stack, domain and governance needs.
- 3
Interview and choose
Run your own technical or domain conversation. Nobody starts without your approval.
- 4
Onboard and deliver
Access, tooling and reporting are set up and the engagement begins on the agreed date.
Senior architects review each requirement and propose placements on technical fit, domain and governance fit, communication and confidentiality. Delivery can be coordinated by a project manager from our team, and deliverables and IP are assigned to you under contract. Pricing follows project scope, duration and the seniority required. See the AI Agent Development & Automation service for project-based work, or read about our full staff augmentation models.
Start a conversation
Tell us what you need. We reply within one business day.
Share a few details and a senior member of our team will come back with questions, matched profiles or a proposed approach. NDA available on request.
- Reply within one business day
- NDA signed before you share details
- Speak directly with a senior architect or engineer
Prefer to share a detailed brief? Use the full project form or explore the talent catalogue.
Questions
Straight answers before we start.
How we work, what we staff and how engagements are structured. For anything else, write to us.
Read before you engage
- RAG vs Fine-Tuning for Regulated Enterprise Data
Retrieval-augmented generation and fine-tuning solve different problems. For regulated, frequently changing knowledge, the choice has consequences for auditability, access control and cost of change.