Hire the best Machine Learning Engineer

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Every profile is screened and verified before it reaches your shortlist. Placeholder profiles shown below - replace with your own anonymised pipeline data.

Angie Z.

Dubai, United Arab Emirates

6 years experience

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Available in 2 weeks

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Min H.

Dubai, United Arab Emirates

4 years experience

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Sohail M.

Abu Dhabi, United Arab Emirates

9 years experience

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Available in 4 weeks

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Peng Z.

Dubai, United Arab Emirates

3 years experience

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Andrew C.

Sharjah, United Arab Emirates

7 years experience

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Xinran L.

Dubai, United Arab Emirates

5 years experience

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How it works

Share the brief

Tell us the role, the must-haves and the budget. We turn that into a scorecard your interviewers actually use.

Get a shortlist

Candidates are screened against the scorecard rather than keyword-matched, so every profile is worth your time.

Interview with structure

Same questions, same rubric, every candidate. Scheduling, panels and scoring all run in one place.

Make the offer

Compare scored candidates side by side, then track the offer through acceptance to the agreed start date.

About the role

Source and shortlist

Structured interview

Progression and salary

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About the role

Job Title: Machine Learning Engineer
Job Summary: We are looking for an experienced Machine Learning Engineer to help us build scalable and accurate machine learning models to drive business outcomes. As part of our team, you will develop algorithms, implement models, and deploy them in production. You’ll collaborate with data scientists, software engineers, and stakeholders to ensure that machine learning solutions are optimized for performance and efficiency. This role offers the opportunity to work on innovative projects in the technology, finance, and healthcare sectors.
Key Responsibilities:
- Develop and implement machine learning models for classification, regression, and clustering tasks.
- Collaborate with data scientists to preprocess data, extract features, and build models using Python and libraries such as TensorFlow and PyTorch.
- Design, build, and maintain scalable model pipelines that can be integrated into production environments.
- Optimize machine learning models for accuracy, performance, and scalability.
- Work closely with software engineers to deploy machine learning models and ensure smooth integration with existing systems.
- Monitor and improve the performance of deployed models through regular evaluations and updates.
- Stay up-to-date with the latest trends and advancements in machine learning and AI.
Requirements:
- Bachelor’s or Master’s Degree in Computer Science, Data Science, Engineering, or a related field.
- 2+ years of experience in developing and deploying machine learning models.
- Strong programming skills in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and scikit-learn.
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with cloud platforms such as AWS, GCP, or Azure for deploying machine learning models.
- Knowledge of machine learning algorithms (e.g., linear regression, decision trees, neural networks, clustering).
- Experience with model deployment and integration into production systems.
- Strong problem-solving skills and the ability to work in a collaborative team environment.
Must-Have Skills:
- Expertise in machine learning algorithms and experience building models for predictive analytics, classification, or clustering.
- Proficiency in Python and data analysis tools such as Pandas and NumPy.
- Experience with deep learning frameworks like TensorFlow or PyTorch.
- Knowledge of cloud platforms for model deployment and scaling.
- Ability to analyze and preprocess large datasets for model training.
Soft Skills:
- Analytical Thinking: Ability to approach complex problems with a logical mindset and break them down into solvable components.
- Problem-Solving: Capable of identifying issues within machine learning models and implementing effective solutions.
- Communication Skills: Able to explain technical concepts to non-technical stakeholders and collaborate across departments.
- Attention to Detail: Precise in analyzing data, developing models, and ensuring models meet accuracy standards.
- Adaptability: Willingness to learn and apply new technologies as the field of machine learning evolves.
Hard Skills:
- Machine Learning Algorithms: Proficiency in building models using algorithms such as decision trees, random forests, neural networks, and clustering techniques.
- Data Analysis: Strong background in data cleaning, preprocessing, and feature engineering to build accurate models.
- Python / R: Experience in programming with Python (or R), along with machine learning libraries like TensorFlow, scikit-learn, and PyTorch.
- Model Deployment: Experience deploying machine learning models into production environments using cloud platforms or containerization (e.g., Docker).

Source and shortlist

Professional network
- Leverage your professional network and reach out to former colleagues, industry peers, and tech community members to ask for referrals.

Educational Institutions:
- Bootcamps: Programs like Udacity, Coursera, or Linux Foundation Training offer certifications in machine learning. Graduates from these programs often have hands-on experience.
Company Career Pages:
- Post job listings on your company’s website and promote them through your social media channels. Candidates often check company career pages directly for opportunities.

Job Boards
- US
  - Indeed (indeed.com): Offers a wide range of engineering job postings.
  - Glassdoor (glassdoor.com): A job board combined with company reviews and salaries.
  - EngineerJobs (engineerjobs.com): Dedicated to engineering roles, including Machine Learning Engineers.
- India
  - Naukri (naukri.com): The largest job portal in India with a focus on engineering roles.
  - Shine (shine.com): Another popular Indian job board for engineering positions.
  - Monster India (monsterindia.com): Widely used for engineering jobs in India.
- UAE & KSA
  - Bayt (bayt.com): A popular job portal for roles in the Middle East, including engineering.
  - GulfTalent (gulftalent.com): A job site specific to the Gulf region.
  - Naukrigulf (naukrigulf.com): Tailored to Gulf countries and suitable for engineering roles.
- Remote Positions
  - We Work Remotely (weworkremotely.com): A popular platform for remote engineering jobs.
  - RemoteOK (remoteok.com): Another platform that lists remote engineering roles.

Structured interview

Question: Can you explain the steps you followed in cleaning and preprocessing the dataset for your model?
- Expected Answer: The candidate should describe their data cleaning process (e.g., handling missing values, normalizing or scaling features) and feature selection techniques.
- Sample Answer: "I first handled missing values by filling them using the median, then scaled the numerical features using standardization. I also performed feature engineering by creating interaction terms for relevant features."
Question: Why did you choose [specific model] for your task, and what other models did you consider?
- Expected Answer: The candidate should explain why they chose a specific machine learning model and compare it with other potential models. They should also mention if they tuned hyperparameters.
- Sample Answer: "I chose Random Forest because it handles missing data well and is less prone to overfitting compared to a decision tree. I also considered using XGBoost but found that Random Forest gave better results on this dataset."
Question: How did you evaluate the performance of your model, and which metric(s) did you use?
- Expected Answer: The candidate should mention using relevant performance metrics and explain why they chose those specific metrics (e.g., accuracy, F1-score, precision-recall).‍
- Sample Answer: "Since the dataset was imbalanced, I focused on the F1-score as it balances precision and recall. I also used a confusion matrix to identify false positives and false negatives."

Progression and salary

Level	United States (USD)	Europe (EUR)	India (INR)	UAE (AED)
Junior Machine Learning Engineer	$70,000 - $90,000	€55,000 - €70,000 (€61,000 - €78,000)	₹8,00,000 - ₹12,00,000 ($9,600 - $14,500)	AED 160,000 - AED 220,000 ($43,500 - $60,000)
Machine Learning Engineer	$90,000 - $130,000	€70,000 - €95,000 (€78,000 - €105,000)	₹12,00,000 - ₹20,00,000 ($14,500 - $24,000)	AED 220,000 - AED 320,000 ($60,000 - $87,000)
Senior Machine Learning Engineer	$130,000 - $160,000	€95,000 - €120,000 (€105,000 - €134,000)	₹20,00,000 - ₹30,00,000 ($24,000 - $36,000)	AED 320,000 - AED 450,000 ($87,000 - $123,000)
Lead Machine Learning Engineer	$160,000 - $200,000	€120,000 - €150,000 (€134,000 - €168,000)	₹30,00,000 - ₹40,00,000 ($36,000 - $48,000)	AED 450,000 - AED 550,000 ($123,000 - $150,000)
AI Architect / ML Architect	$200,000 - $240,000	€150,000 - €180,000 (€168,000 - €201,000)	₹40,00,000 - ₹50,00,000 ($48,000 - $60,000)	AED 550,000 - AED 700,000 ($150,000 - $190,000)

customer stories

Hear from our customers

Whitecarrot’s ATS platform has made a significant impact on our recruitment process. It’s easy to use and has streamlined our interview scheduling and candidate evaluations. We’re excited to continue using it and seeing the results.

Sabrine

ZEOF Group

We’ve been using Whitecarrot for all our job openings this year, and the experience has been excellent. The platform has made our recruitment process more efficient, and everyone is happy with the results.

Karl

Careem

Whitecarrot’s ATS has been a game-changer. It’s user-friendly, streamlines recruitment, and offers responsive support. Their growth-driven approach makes it invaluable. Highly recommended!

Rasha

Bayzat

Whitecarrot’s ATS has transformed our hiring process. It’s intuitive and saves us so much time. The platform’s efficiency and excellent support have helped us manage recruitment smoothly. Highly recommend it!

John

Syncsphere

We’ve seen significant improvements in our recruitment process since adopting Whitecarrot. The platform is easy to navigate, and the support team is always responsive. It’s a game-changer for our hiring efforts!

Emily

Nexanode

Sabrine

ZEOF Group

Karl

Careem

Whitecarrot’s ATS has been a game-changer. It’s user-friendly, streamlines recruitment, and offers responsive support. Their growth-driven approach makes it invaluable. Highly recommended!