Hire ML Engineers in Surrey
Data-driven machine learning at scale
ML engineers who build, train, and deploy machine learning models in production. Expertise in model development, MLOps, and data pipelines.
Surrey is Metro Vancouver's largest city and fastest-growing technology hub — home to Surrey Memorial Hospital's major expansion, Simon Fraser University's growing Surrey campus, and an emerging tech sector attracted by significantly lower costs than Vancouver.
What You Get
Available seniority levels.
From junior developers to staff engineers, we have ml engineers at every experience level.
Mid-Level (3-5 years)
Senior (5-8 years)
Lead/Staff (8+ years)
Principal (10+ years)
Core skills.
Our ml engineers come with expertise in these essential technologies and practices.
Hire Now →What they do.
Key responsibilities and deliverables you can expect from a ml engineer.
Why hire a ml engineer?
The unique value a ml engineer brings to your team.
Model development expertise
MLOps pipeline design
Feature engineering skills
A/B testing methodology
Production ML deployment
Flexible engagement.
Choose the model that fits your needs and budget.
Full-time dedicated
Part-time (20 hrs/week)
Contract-to-hire
Project-based
Success Stories
Real results from teams augmented with our ml engineers
MLOps Platform for Autonomous Vehicle Company
Challenge
An AV company was training hundreds of models but lacked infrastructure for versioning, deployment, and monitoring. Data scientists spent 40% of time on ops instead of research.
Solution
We built a complete MLOps platform with experiment tracking, model registry, automated training pipelines, A/B testing infrastructure, and comprehensive monitoring.
Outcome
Model deployment time reduced from weeks to hours. Data scientist productivity increased 60%. Now managing 200+ models in production with full lineage.
Computer Vision Quality Inspection for Manufacturing
Challenge
A manufacturing company was losing $2M annually due to defective products reaching customers. Manual inspection was slow and inconsistent, catching only 85% of defects.
Solution
Our AI engineers developed a computer vision system using custom-trained models to detect defects in real-time on the production line. The system integrates with existing PLCs for automated rejection.
Outcome
Defect detection rate improved to 99.2%. Inspection throughput increased 10x. Annual savings from reduced returns and warranty claims exceeded $1.8M.
Frequently Asked Questions
What does an ML Engineer do?
ML Engineers build and deploy machine learning models at scale, including data pipelines, model training, and production deployment systems.
How do ML Engineers differ from Data Scientists?
ML Engineers focus on productionizing models and building scalable ML systems, while Data Scientists focus more on experimentation and analysis.
What MLOps practices do ML Engineers follow?
Our ML Engineers implement CI/CD for ML, model versioning, A/B testing, monitoring, and automated retraining pipelines.
Can ML Engineers work with big data?
Yes, they have experience with distributed computing using Spark, Dask, and cloud-native solutions for large-scale data processing.
Do ML Engineers handle model monitoring?
Yes, they implement drift detection, performance monitoring, and alerting to ensure models perform well in production.
How quickly can you provide developers?
We can typically match you with pre-vetted developers within 48-72 hours. For specialized roles, it may take up to 1 week to find the perfect fit.
What is your vetting process for developers?
Our vetting process includes: technical assessments, live coding interviews, English proficiency tests, portfolio review, and reference checks. Only the top 3% of applicants pass our screening.
Can I interview the developers before hiring?
Absolutely. You can conduct your own technical interviews, cultural fit assessments, and trial projects before making a commitment. We encourage this to ensure the best match.
What engagement models do you offer?
We offer full-time dedicated (160 hrs/month), part-time (80 hrs/month), and hourly arrangements. All developers work exclusively on your projects during their contracted hours.
How do you handle timezone differences?
Our developers align their working hours with US/Canada business hours (EST, CST, PST). You get 4-6 hours of real-time overlap daily for meetings and collaboration.
What if a developer is not a good fit?
We offer a 2-week risk-free trial. If you are not satisfied, we will replace the developer at no additional cost. Your satisfaction is guaranteed.
How do billing and payments work?
We bill monthly in advance. You receive detailed timesheets and can track hours through our project management tools. We accept wire transfers, ACH, and credit cards.
Do you provide project managers?
Yes, every engagement includes a dedicated account manager who handles onboarding, communication, and ensures smooth collaboration between you and your developers.
What technologies do your developers specialize in?
Our talent pool covers the full modern stack: React, Node.js, Python, Go, TypeScript, AWS, GCP, Azure, mobile (iOS/Android), AI/ML, DevOps, and more.
Can developers sign NDAs and work under our security policies?
Yes. All our developers sign NDAs, and we can accommodate your specific security requirements including VPNs, compliance certifications, and access controls.
Ready to hire a ml engineer?
Tell us about your project requirements and we'll match you with the perfect candidate.
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