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 — from concept to deployment.
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Top 1%of software development companies on Clutch
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EU GDPRcommitment to security & privacy
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60%of business is based on customer referrals
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ISO 27001data security certification by Bureau Veritas
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EY EoY 2023EY Entrepreneur of the Year in West Sweden
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 to 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 some 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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You rely on manual processes that could be automated with intelligent systems. Experiments stay stuck in notebooks. You need production-ready ML pipelines.
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Accuracy and performance matter. Out-of-the-box models don’t cut it anymore.
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 & 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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Natural Language Processing & 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 & 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 & 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 in dynamic environments.
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Cleaning, Annotation & 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 dedicated annotation teams to ensure your models learn from the right inputs.
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Data Engineering & Scalable Infrastructure
Power your ML workloads with robust data pipelines and infrastructure. We design and implement scalable, secure platforms that handle data ingestion, transformation, and storage — all optimized for model performance and compliance.
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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.
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Database Optimization & Data Pipeline Development
Streamline backend operations to support machine learning. We optimize your databases and build fault-tolerant, efficient pipelines that deliver clean, real-time data to your models.
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Anomaly Detection & 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.
How much does it cost to hire a dedicated machine learning developer?
The cost to hire remote machine learning engineers depends on several key factors: the level of expertise required, the complexity of your project, and the region where the engineers are based. Rates in Northern and Western Europe tend to be higher than those in Eastern Europe or Southeast Asia. Specialized skills in areas like deep learning or MLOps can also influence pricing, especially for more complex or long-term projects.
When it comes to actual numbers, you’re looking at around $180 per day ($3,400 monthly) for junior ML talent on shorter engagements, though this drops to about $2,550 monthly if you’re willing to commit long-term. Mid-level engineers with a few years of solid experience typically start around $290 daily ($5,500 monthly) for short-to-mid-term work, but can be secured for approximately $4,150 monthly with longer contracts. Senior specialists who bring deep expertise and leadership to the table expect to invest $435 daily ($8,250 monthly) on shorter projects or $6,200 monthly for extended engagements. These investments tend to pay off in terms of quality and efficiency when implementing ML solutions.
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Junior
For junior ML specialists, our rates start at $180 per day, which translates to approximately $3400 per month for short-to-mid-term team collaborations. For longer-term cooperation, the monthly rate begins at $2550.
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Middle
Engaging mid-level ML engineers starts at $290 per day (around $5500 per month) for short-to-mid-term projects, while long-term engagements begin at a monthly rate of $4150.
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Senior
For senior-level Machine Learning expertise, our daily rates start from $435 (approximately $8250 per month) for short-to-mid-term needs, and for sustained, long-term partnerships, the monthly investment begins at $6200.
Freelancers vs. white-label tech partner? A practical comparison for smart hiring.
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.
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Need help choosing the right approach for your team? Let’s explore your goals and see what setup works best.
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
Direct communication and controlGet 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
End-to-end supportNeed to move fast on a specific challenge or initiative? We’ll 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
Hands-on team trainingEmpower your team with practical, hands-on workshops tailored to your needs. One of our standout offerings is the Green Coding workshop, which focuses on sustainable and eco-friendly coding practices.
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
When you hire a machine learning engineer through Beetroot, our 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
At this stage, we guide each candidate through a role-specific skills matrix, testing everything from hands-on problem-solving to architectural decision-making. Real-world challenges reveal who can design production-ready machine-learning pipelines. For an additional layer of insight, we can assign an optional take-home task that mirrors the work they’d tackle for you, giving you extra confidence before finalizing the hire.
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Curating a dynamic database
Profiles include only those cleared through our screening process. We filter candidates by tech stack, seniority, and readiness to onboard to easily match you with pre-screened candidates.
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. We offer 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.
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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.
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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.
