Hire Machine Learning Engineers
Hire machine learning engineers with Beetroot to build AI systems that deliver measurable results. Our specialists bring extensive expertise in computer vision, natural language processing, and MLOps, along with a strong focus on real-world impact, to turn your ideas into production-ready AI solutions.
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Top 1% of global
Software Service providers -
ISO 27001 certification
by Bureau Veritas
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GDPR-Compliant processes
for responsible data protection -
AWS trusted infrastructure
for scalable solutions -
Bureau Veritas —
an independent global leader in testing, inspection, and certification.
Hire Machine Learning Experts From Beetroot
Need help turning complex data into actionable insights? Hire ML engineers from Beetroot to get the job done. Our team brings hands-on experience and practical know-how, from building custom algorithms to deploying scalable predictive services that support your business growth.
When do you need a machine learning engineer?
If your churn-prediction dashboard lags by 24 hours or your compliance team can’t explain model decisions, you’re past the experimentation stage. Hire machine learning developers to translate notebooks into monitored pipelines, so your team iterates weekly instead of quarterly. Here are key scenarios where skilled ML engineers can help:
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Models break silently or drift over time
Your team lacks the monitoring and retraining infrastructure to keep ML systems accurate and reliable in production.
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Manual processes could be automated
You rely on manual processes that intelligent systems could handle faster, more consistently, and at a lower cost.
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Experiments stay stuck in notebooks
Promising prototypes never reach users, and you need production-ready ML pipelines to move them forward.
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Accuracy and performance matter
Out-of-the-box models don’t cut it anymore, and you need custom models tuned to your data and quality targets.
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Bring intelligence to your product with Beetroot:
Our Machine Learning Engineering Services
From prototypes to production-ready systems, our ML engineers handle the complexity of AI, so your team can stay focused on product growth. We help you build smart, scalable, and secure machine learning solutions without slowing down your roadmap.
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Machine Learning and Predictive Modeling
Design and deploy ML models that solve real-world problems with support from our experienced engineers. From classification and regression to forecasting and recommender systems, we balance accuracy, speed, and explainability.
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NLP and Large Language Models (LLMs)
Turn unstructured text into actionable insight with custom NLP pipelines and fine-tuned LLMs. Automate sentiment analysis, chatbots, summarization, and content generation to deliver personalized, human-like experiences at scale.
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Computer Vision and Image Intelligence
Build systems that see and interpret the world through deep learning. Apply object detection, face recognition, scene segmentation, and video analysis to power solutions in healthcare, retail, manufacturing, and beyond.
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Reinforcement Learning and Intelligent Decision Systems
Train systems to learn by doing, ideal for robotics, simulations, and adaptive control. Our engineers build reinforcement learning models that optimize performance through trial, error, and continuous feedback.
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Data Cleaning, Annotation, and Feature Engineering
Clean, well-labeled data is the foundation of any ML project. Our engineers build automated cleaning pipelines, define labeling guidelines, and design custom features, coordinating with annotation teams so your models learn from the right inputs.
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Data Engineering and Pipeline Development
Power your ML workloads with robust, scalable data infrastructure. We optimize your databases and build secure, fault-tolerant pipelines for data ingestion, transformation, and storage that deliver clean, real-time data to your models.
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Tabular Data Analysis
Leverage structured data to drive smarter decisions. Our ML engineers extract insights from databases, spreadsheets, and logs to support forecasting, KPI tracking, and data-driven strategy across your business.
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Anomaly Detection and Risk Scoring
Spot issues before they escalate with real-time risk detection. We create systems that identify anomalies, flag operational risks, and support use cases like fraud prevention, predictive maintenance, and alerting.
Find the right ML expertise for your use case:
How much does it cost to hire a dedicated machine learning developer?
The cost to hire remote machine learning engineers depends on the level of expertise required, the complexity of your project, and the engagement duration. Specialized skills in areas like deep learning or MLOps can also influence pricing, especially for more complex or long-term projects.
These investments tend to pay off in quality and efficiency when implementing ML solutions.
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Entry-level and supporting engineers start at $229 per day, or approximately $4,350 per month for short-to-mid-term engagements. For long-term engagements, rates start at $3,625 per month.
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Mid-level positions start at $411 per day, or approximately $7,800 per month for short-to-mid-term projects. For long-term engagements, rates start at $6,500 per month.
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Senior specialists start at $529 per day, or approximately $10,050 per month for short-to-mid-term projects. For long-term engagements, rates start at $8,375 per month.
Cooperation Types
Whether you’re building complex ML systems or looking to strengthen your team’s skills, we offer flexible cooperation models to match your goals. Choose the best setup for your timeline, budget, and internal capabilities.
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Dedicated Development Teams
Best for long-term partnershipGet a team of experienced engineers fully dedicated to your project. They integrate into your workflow, bring deep technical know-how, and stay aligned with your evolving product goals from day one.
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Project-Based Engagements
Suited to specific, time-bound goalsNeed to move fast on a specific challenge or initiative? We bring the right people and tools to the table, from discovery and planning to delivery and handover, ensuring outcomes without the overhead.
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Custom Tech Training
Best for upskilling in-house teamsBring in experienced instructors for focused custom tech workshops built around the areas where your team needs extra depth. The format can combine practical exercises, discussion, and guidance that your team can apply in day-to-day work.
Not sure which model fits? Tell us about your ML goals:
How We Build High-Performing Teams Step by Step
Our hiring process goes beyond checking boxes. We combine deep technical screening with real-world team-fit evaluation to help you onboard engineers who are skilled, reliable, and ready to contribute from day one.
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Initial Screening by Recruiters
Step 1Our recruitment team delivers candidates already matched to your domain and vetted for technical skills, English fluency, time-zone overlap, and culture fit, ready to integrate with your team and workflows.
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Technical Screening by Tech Leads
Step 2Candidates go through a role-specific skills matrix, from hands-on problem-solving to architectural decisions, with real-world challenges in production ML pipelines and an optional take-home task that mirrors your work.
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Curating a Dynamic Database
Step 3Profiles include only those cleared through our screening process. We filter candidates by tech stack, seniority, and readiness to onboard, so we can quickly match you with pre-screened engineers.
Freelancers vs. White-Label Tech Partner: A Practical Comparison
Whether you’re launching a new product, scaling an existing platform, or filling skill gaps, choosing the right collaboration model is key. Below is a comparison to help you evaluate which setup aligns best with your project goals, team capacity, and long-term vision.
Freelance Specialists
- Fast onboarding
- Budget-friendly for short tasks
- Flexible for ad-hoc support
White-Label Tech Partner
- Structured teams
- Reliable delivery
- Scalable resources
- Full-cycle project execution
Freelance Specialists
- May require extra oversight
- Inconsistent availability
- Limited long-term value
White-Label Tech Partner
- Higher initial coordination
- Best for defined scopes or ongoing collaboration
Freelance Specialists
- Specialized one-off tasks
- Prototypes
- Urgent fixes
White-Label Tech Partner
- Multi-phase projects
- Continuous delivery
- Strategic initiatives requiring consistency
Need help choosing the right approach for your team? Let’s explore your goals and see what setup works best.
Why hire machine learning engineers from Beetroot?
From discovery to deployment, Beetroot helps you integrate machine learning in a way that fits your tech stack, team dynamics, and business goals. With a Swedish headquarters and delivery locations in Europe and Vietnam, we bring together technical depth and a partnership-first mindset to deliver real, lasting value.
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Security-First AI Development
We embed security into every layer of the ML lifecycle, from data handling and model training to deployment and monitoring, keeping your systems safe by design.
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Sustainable by Design
Our engineers follow energy-efficient practices and encourage responsible AI use, helping you build impactful solutions without compromising your sustainability goals.
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Built for Long-Term Growth
Beyond building models, we focus on building capacity, offering team augmentation, milestone-based development, and custom training to help your business grow.
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Cloud-Native Flexibility
We work across AWS, Azure, and GCP to build scalable, vendor-agnostic machine learning solutions that meet your infrastructure needs and avoid lock-in.
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Reliable Global Delivery
Our hybrid delivery model and remote collaboration practices ensure smooth integration with your team, wherever you’re based and whatever your time zone.
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All-in-One ML Enablement
From initial research and prototyping to deployment and MLOps, we support every stage of your ML journey, scaling with you as your product evolves.
What Our Clients Say
Real stories from the companies we’ve teamed up with: how we work, what we solve, and why they choose Beetroot.
Featured Cases
While some of our collaborations are under NDA, the stories we can share reflect our ability to tackle complex challenges and deliver real-world impact through tailored tech solutions.
Let’s Build Your Next AI-Powered Solution
Need to hire ML developers to move your AI project forward? Share a few details, and our team will match you with experienced engineers tailored to your goals. Fill out the form to get started.
FAQs
Wondering what to expect when hiring ML engineers? Here are a few practical answers about onboarding, candidate selection, deep learning, and MLOps.
