Hire Dedicated ML Engineers As Per Experience

01

Junior ML Engineer

  • 1-2 Years’ Experience
  • Proficient in core ML algo(linear/logistic regression, decision trees, SVM).
  • Strong knowledge of Python & ML libraries (scikit-learn, NumPy, Pandas, Matplotlib).
  • Familiar with data preprocessing, feature engineering, & evaluation metrics.

02

Senior ML Engineer

  • 2+ years’ experience
  • Expertise in building complete ML solutions, from data collection to deployment.
  • Proficient in deep learning frameworks (TensorFlow, Keras, PyTorch, MXNet).
  • Skilled in hyperparameter tuning, optimization, & cloud ML platforms.

03

Lead ML Engineer

  • 5+ years’ experience
  • Advanced expertise in ML algorithms (Reinforcement Learning, GANs, NLP).
  • Skilled in deploying scaled models to ensure reliability in production.
  • Knowledge of MLOps principles, model versioning, CI/CD, & model monitoring

Your data has a story to tell. Let our ML Engineers translate it

Leverage our expertise to build machine learning models that evolve with your data and power your next-gen applications.

Hire ML Engineers Now!

Our ML Engineers Expertise

Our ML Engineers specialize in designing, developing, and deploying scalable machine learning models tailored to your business needs. With expertise in data preprocessing, model training, optimization, and cloud integration, they ensure high-performance AI solutions that drive real impact.

ML Consulting & Advisory

Get expert guidance on leveraging machine learning to address your business challenges. From strategy to implementation, we help you maximize the ROI of your ML initiatives.

Custom ML Development

Design and develop bespoke machine learning solutions tailored to your business needs, ensuring scalability, efficiency, and high performance.

ML Algorithm Development

Craft and fine-tune machine learning algorithms to improve accuracy, speed, and scalability for complex business problems.

MLOps Workflows

Streamline your machine learning workflows with robust MLOps practices. We ensure efficient model deployment, monitoring, and automation for scalable and reliable solutions.

Precision-Driven ML Modeling

Build precise and high-performance models using cutting-edge techniques to solve your most critical business problems.

Model Optimization & Hyperparameter Tuning

We ensure that your models achieve the highest performance by applying hyperparameter tuning techniques like GridSearchCV, RandomizedSearchCV, and Bayesian Optimization to refine the models.

Model Deployment

Our ML engineers have expertise in deploying models to production using technologies like Docker, Kubernetes, Flask, FastAPI, and AWS services, ensuring efficient and scalable model execution.

Deep Learning & Neural Networks

Our engineers are proficient in building deep learning models for a variety of tasks, including computer vision, NLP, and predictive analytics. We work with frameworks such as TensorFlow, PyTorch, and Keras to create cutting-edge models.

Data Engineering & Feature Engineering

We design data pipelines and conduct feature engineering to prepare your data for model training, ensuring high-quality inputs for accurate predictions.

ML Cloud Integration

Harness the power of cloud platforms like AWS, Azure, and Google Cloud for scalable, secure, and efficient machine learning solutions.

Ongoing ML Support and Maintenance

We offer dedicated support and maintenance services to monitor your machine learning models, address issues, and ensure seamless operation over time.

Core Capabilities of Our Machine Learning Engineers

Predictive Analytics

Develop models to forecast trends, customer behavior, or business outcomes, enabling data-driven decision-making.

Recommendation Systems

Build personalized recommendation engines for eCommerce, streaming platforms, and more to enhance user experience and engagement.

Computer Vision

Create solutions for object detection, image classification, facial recognition, and video analysis across industries like healthcare, retail, and security.

Natural Language Processing (NLP)

Implement applications such as chatbots, sentiment analysis, language translation, and document summarization.

Fraud Detection

Develop ML models to detect anomalies and fraudulent activities in industries like banking, insurance, and eCommerce.

Autonomous Systems

Work on self-driving vehicles, drones, or robotic systems that rely on real-time data and decision-making.

Sentiment & Social Media Analysis

Analyze public sentiment, track brand reputation, and extract insights from social media data.

Dynamic Pricing

Implement algorithms for real-time pricing adjustments in eCommerce, travel, and hospitality industries.

Conversion AI

Build intelligent, context-aware chatbots for customer support and engagement using NLP and reinforcement learning.

Our Flexible Engagement Models

Hourly Hiring

Start work in 48 hours

Duration

8 Hrs/Day

Minimum Days

30 Days

Billing

Monthly

Full Time Hiring

Start work in 72 hours

Duration

8 Hrs/Day

Minimum Days

30 Days

Billing

Monthly

Part Time Hiring

Start work in 48 hours

Duration

80 Hrs/Month

Minimum Days

30 Days

Billing

Monthly

AI adoption has grown by 270% in the last 4 years - Are you keeping up?

Don't fall behind - Accelerate AI adoption with our skilled ML engineers tailored to your needs.

Stay Ahead with ML Experts!

Hire ML Engineers in 4 Easy Steps

Choose Your
Engagement Model

Select Full-Time, Part-Time, or Hourly engagement based on your project’s requirements and timeline.

Screen & Select
ML Engineers

Browse through ML engineers’ profiles, focusing on expertise in data science, model building, and cloud integration.

Conduct
One-on-One Interview

Evaluate candidates’ technical skills by asking about their experience in data preprocessing, model evaluation, and model deployment.

Onboard
ML Engineers

The selected candidate will integrate into your team within 24–48 hours, enabling a quick start to your machine learning project.

Why Hire Machine Learning Engineer from Aglowid?

48 Hours Talent Integration

Onboard ML engineers within 48 hours for a swift project kick-off.

Advanced ML Expertise

Our engineers are proficient in supervised, unsupervised, and deep learning algorithms, ensuring the best solutions for your business.

Cloud Integration

Deploy models on cloud platforms like AWS, Google Cloud, and Azure for seamless scalability and performance.

End-to-End ML Development

We cover the complete lifecycle of ML models, from data preprocessing to deployment and monitoring.

Transparent Pricing

With a pay-as-you-go model and no hidden fees, we offer flexible billing options for your convenience.

Proven Track Record

A 98% retention rate demonstrates our commitment to delivering high-quality, long-term ML solutions.

Quality Assurance

We ensure model performance, scalability, and accuracy at every stage of development and deployment.

Scalable & Flexible Team

Quickly scale your ML team up or down with flexible engagement models, ensuring agility and efficiency as your project evolves.

Hire ML Engineers from Aglowid vs. In-House vs. Freelance

In-House Freelancer
Hiring Model Full Time Monthly, PartTime & Full-time Weekly, Hourly
Time to Get Right Developers 4 - 12 weeks 1 day - 2 weeks 1 - 12 weeks
Time to Start a Project 2 - 10 weeks 1 day - 2 weeks 1 - 10 weeks
Recurring Cost of Training & Benefits $10,000 -$30,000 0 0
Time to Scale Size of the Team 4 - 16 weeks 48 hours - 1 week 1 - 12 weeks
Pricing (weekly average) 2.5 X 1.5 X 1 X
Project Failure Risk Low Extremely low, we have a 98% success ratio Very High
Developers Backed by a Delivery Team Some Yes No
Shadow Resource Costly Yes No
Project Manager Extra Cost Minimal cost No
Query Support High 24 Hours Assurance No
Tools & Environment Depend on Team High Uncertain
Agile Development Methodology May Be Yes No
Impact Due to Turnover High None High
Structured Training Programs Some Yes No
Communications Seamless Seamless Uncertain
Termination Costs High None None

FAQs - Questions to Ask Before Hiring Angular Developers

The cost of hiring an ML developer varies depending on the project scope, developer experience, and the engagement model. We offer customized pricing based on your specific needs, so please reach out for a tailored quote.

We can have an ML developer onboarded and working on your project in as little as 48 hours. Our streamlined process ensures quick and efficient integration.

Yes! We offer scalable engagement models that allow you to expand or contract your team of ML developers based on the evolving needs of your project.

Yes, we understand the importance of confidentiality. We sign a Non-Disclosure Agreement (NDA) to protect your data, proprietary algorithms, and intellectual property throughout the development process.

Yes, we offer flexible engagement models such as hourly, part-time, and full-time hiring, allowing you to scale the team based on your project’s duration and requirements.

Not at all! We will guide you through the process, breaking down complex ML concepts into simple terms and ensuring the solution we develop aligns with your business goals.

It’s easy! Simply share your project requirements with us, and we’ll recommend the best ML developer(s) for your needs. You can schedule an interview and get started with your project in just 48 hours.

We implement model monitoring tools like MLflow and TensorBoard to track model performance in real-time. If necessary, we retrain models to maintain accuracy and relevance as new data becomes available.

Yes, we leverage cloud-based services such as AWS, Azure, and Google Cloud for model deployment. This ensures scalability, high availability, and easy management of models in production environments.

We follow best practices in data encryption, secure access control, and model robustness to ensure the security of both the data and the ML model. Additionally, we adhere to relevant GDPR, HIPAA, and data protection standards throughout development.

Our developers are experts in big data frameworks like Apache Spark, Hadoop, and Dask. We use distributed computing techniques to handle large datasets efficiently and scale machine learning workflows for massive data volumes.

Yes! Our ML developers integrate models seamlessly into your existing systems using APIs, microservices, and cloud platforms like AWS SageMaker, Google Cloud AI, and Azure ML, ensuring smooth interoperability with your current infrastructure.

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Testimonials

Our Slam Book

Tony Lehtimaki

DIRECTOR - AMEOS

Spain

Very professional, accurate and efficient team despite all the changes I had them do. I look forward to working with them again.

Antoine de Bausset

CEO - BEESPOKE

France

They are great at what they do. Very easy to communicate with and they came through faster than I hoped. They delivered everything I wanted and more! I will certainly use them again!

Vivek Singh

MARKETING & SALES HEAD - VARMORA

Gujarat

I really liked their attention to detail and their sheer will to do the job at hand as good as possible beyond professional boundaries.

Nimesh Patel

DIRECTOR - COVERTEK CERAMICA

Gujarat

Excellent work, and on time with all goals. Communication was very easy, and knowledge of work was excellent. Will be working with them on upcoming projects. I highly recommend.

Craig Zappa

DIRECTOR - ENA PARAMUS

United States

"I would like to recommend their name to one and all. No doubt" their web app development services cater to all needs.

Neil Lockwood

CO-FOUNDER - ESR

Australia

Aglowid is doing a great job in the field of web app development. I am truly satisfied with their quality of service.

Daphne Christoforidou

CEO - ELEMENTIA

United States

Their team of experts jotted down every need of mine and turned them into a high performing web application within no time. Just superb!

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