[ Machine learning, on demand ]
Hire machine learning engineers and ML consultants, matched in minutes
Describe the model you need in plain language: a forecast, a scoring model, a recommendation engine, an ML pipeline. Botgigs matches you to a vetted machine learning engineer or ML consultant who has shipped that exact kind of system, or a ready-made agent when one already solves it. Same depth as a consulting firm, without the retainer or the day rate.
Free hire brief · No card required · Vetted ML and data specialists
[ HIRE-BRIEF GENERATOR ]
demo · free · no signup · up to 10 briefs per session
brief.json
[ pre-generated sample ]
best-effort AI estimate, not a quote or a match
job
ticket_01
scope of work
who to hire
screen for
effort estimate
questions to ask your hire
- ?
Like the brief? Get matched to the right specialist when we launch.
01 / what they build
What a machine learning engineer actually builds
Machine learning development covers a handful of real problem types, and most projects need one of them done well, not a whole research team. Botgigs vets for these specific skills, so you hire the machine learning engineer whose shipped work matches your problem instead of paying a consulting bench for time you never use.
[ forecast ]
Forecasting and prediction
Demand, revenue, inventory and time-series models that turn your history into numbers you can plan against, with the data prep and backtesting behind them.
[ scoring ]
Scoring and risk models
Fraud, credit, churn and lead-scoring models that rank records by likelihood, tuned for the precision and recall your business actually needs.
[ recommend ]
Recommendation engines
Product, content and next-best-action models that lift conversion and retention, wired into your catalog and event data.
[ nlp ]
NLP, embeddings and search
Classification, extraction and semantic search over your text: tickets, documents and reviews turned into structured signals and better retrieval.
[ vision ]
Computer vision
Detection, classification and OCR on images and video for quality control, document processing and monitoring use cases.
[ mlops ]
ML pipelines and MLOps
The plumbing that makes a model production software: training pipelines, an inference service, versioning, and monitoring that flags drift before it costs you.
02 / why botgigs
Machine learning consulting depth, without the firm's day rate
01
Hire the engineer, not the bench
You work directly with the machine learning engineer building your model, so there is no account manager between you and the person who understands your data, and no firm margin stacked on their rate.
02
Scoped before you spend
The hire brief turns your problem into deliverables, a modeling approach and an honest effort band up front, so an ML project cannot stall in a paid discovery phase. See how hiring works.
03
Buy the agent when it fits
Some ML problems are now finished products. When one matches, you hire a working agent instead of paying to train a model from scratch, or build an AI agent to spec when it does not.
04
Vetted on shipped models
The bar is a model that ran in production: what it predicted, at what accuracy, and how they knew when it drifted. Keeping it healthy after launch is a separate discipline, so some teams hire for MLOps and model monitoring instead. Every specialist on the marketplace is screened on evidence, not keywords.
03 / compare the routes
Botgigs vs an ML consulting firm vs an in-house ML hire
Three honest ways to get machine learning built. The US figures below are typical 2026 market ranges, not quotes. Which one fits depends on scope, how much ongoing model work there is, and your compliance needs.
| Route | Time to start | Typical US cost | Best for |
|---|---|---|---|
| Botgigs ML engineer or agent | Days | $80 to $200/hr, or roughly $2,000 to $15,000 per scoped model or pipeline | One clear model or ML build, fast, without firm margin |
| Machine learning consulting firm | Weeks (discovery first) | $150 to $300/hr, or $40,000 to $150,000+ per engagement | Strategy plus build across several teams and systems |
| In-house ML engineer | Months to hire | $130,000 to $220,000 per year, plus 25 to 40% overhead | ML as a core, always-on part of the product |
Need broader AI scope than a single model? Compare the wider AI development services and AI engineering routes.
04 / how it works
From data problem to the right ML hire, in minutes
step_01
Describe the model
What you want to predict or automate, the data you have, and the decision it should drive. The AI turns it into scope: approach, deliverables and the ML specialism to screen for.
step_02
Get scope and matches
A vetted machine learning engineer who has shipped this kind of model, or a ready-made agent if one already fits. No proposal spam, no bidding war.
step_03
Hire and ship
Agree the milestones from the brief and start. Milestone escrow and consistent vetting are part of the planned launch scope.
05 / questions
Machine learning hiring questions, answered
What does a machine learning engineer do?
A machine learning engineer builds, trains and deploys models that make predictions from data: forecasting, fraud and risk scoring, churn prediction, recommendations, and text or image classification. Beyond the model, they own the pipeline that feeds it, the service that serves predictions, and the monitoring that catches drift once it is live.
How much does it cost to hire a machine learning engineer?
In the US, freelance machine learning engineers charge roughly $80 to $200 per hour, and machine learning consulting firms run about $150 to $300 per hour. A single scoped model or pipeline usually lands between $2,000 and $15,000, well below a full-time hire at $130,000 to $220,000 a year plus overhead.
What is the difference between a machine learning engineer and a data scientist?
A data scientist explores data and decides what is worth modeling. A machine learning engineer turns that into production software: training pipelines, an inference service, deployment and monitoring. For a model that has to run reliably inside your systems, you usually want the engineer.
Should I hire a machine learning engineer or an ML consulting firm?
For one well-defined model or pipeline, a single vetted machine learning engineer is faster and cheaper than a firm. Bring in ML consulting when the work spans strategy, several teams and long-term model governance. On Botgigs you start with the specialist and scale up only when scope genuinely grows.
[ Early access ]
Scope your machine learning project before you spend a dollar.
Describe the model in the free hire-brief demo, then join early access to get matched to the right ML engineer or agent at launch.
Launching soon. No card required.
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