Talantix.io
Spotify•16.02.26
AI SCORE 8.5

Remote Machine Learning Engineer II - Ads Forecasting

$120K–$150K/year
RemoteAdTech
Machine Learning•Python•TensorFlow•PyTorch•Data Analysis•A/B Testing•Cloud Computing

About the Role

We are seeking a Remote Machine Learning Engineer II to join our Ads Forecasting team at Spotify. In this role, you will lead strategic initiatives and projects that focus on building and maintaining models and systems to predict future ad inventory, demand, and performance across our platform. As a Remote Machine Learning Engineer II, you will leverage your expertise in machine learning model development, AI engineering, and online experimentation techniques to drive key business decisions and optimize ad delivery.

What You'll Do

  • Develop and maintain machine learning models that enhance ad forecasting accuracy.
  • Collaborate with cross-functional teams to implement data-driven solutions that improve ad performance.
  • Utilize state-of-the-art time-series and predictive modeling techniques to inform business strategies.
  • Conduct online experiments to validate model performance and effectiveness.
  • Analyze large-scale data sets to extract actionable insights and improve forecasting methodologies.

Requirements

  • 3+ years of experience in machine learning engineering or related fields.
  • Strong proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Experience with online experimentation techniques and A/B testing.
  • Familiarity with large-scale engineering systems and data processing.
  • Ability to communicate complex technical concepts to non-technical stakeholders.

Nice to Have

  • Experience in the advertising technology industry.
  • Knowledge of time-series analysis and forecasting techniques.
  • Familiarity with cloud platforms (e.g., AWS, GCP).

What We Offer

  • Competitive salary and benefits package.
  • Flexible remote work environment with a focus on work-life balance.
  • Opportunities for professional development and growth within the company.
  • Collaborative and innovative team culture.
  • Access to cutting-edge technology and tools.
Why This Job8.5 of 10

This Remote Machine Learning Engineer II position at Spotify offers a unique opportunity to work on innovative ad forecasting projects while enjoying a flexible work environment and competitive salary.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficient in building and deploying machine learning models using Python, TensorFlow, and PyTorch, with a strong focus on A/B testing methodologies to evaluate model performance in real-world scenarios.

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Self-motivated and disciplined to work effectively in a fully remote environment, demonstrating strong time management skills and the ability to collaborate asynchronously with cross-functional teams.

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Analytical mindset with a proven track record of conducting data analysis and leveraging cloud computing platforms (like AWS or Google Cloud) for scalable machine learning solutions, ideally with 3-5 years of relevant experience.

Learning Resources

→Deep Learning with Python and PyTorchcourse
→Machine Learning Crash Courseguide
→A/B Testing: The Complete Guidearticle

Career Path

Remote Machine Learning Engineer II - Ads Forecasting(Now)→Machine Learning Engineer III or Data Scientist(1-2 years)→Lead Machine Learning Engineer or AI Product Manager(3-5 years)

Market Overview

Market Size 2024
$21.17B
Annual Growth
38.2%
AI Adoption
75%
Investment
+150%
Labour Demand
+45%
Avg Salary
$120K

Skills & Requirements

Required
Machine LearningPythonTensorFlow
Growing in Demand
Natural Language ProcessingCloud ML Services (AWS SageMaker, Google AI Platform)MLOps
Declining
Traditional Statistical Analysis (e.g., SPSS)R Programming

Domain Trends

Increased Focus on Ethical AI
Companies are prioritizing ethical considerations in AI development, with 67% of organizations implementing AI ethics guidelines.
Integration of AI in Marketing
AI-driven marketing solutions are projected to grow by 32% annually, enhancing targeting and personalization in advertising.
Rise of Automated Machine Learning (AutoML)
The AutoML market is expected to grow by 40% year-over-year, allowing non-experts to leverage machine learning capabilities effectively.

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