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Job DescriptionJob Description About Us
Adora is a rapidly growing Seattle-based SaaS company developing an innovative platform in the trillion-dollar digital advertising industry. Our platform is set to transform the landscape through cutting-edge technology and AI-driven solutions. We're currently in stealth mode and look forward to sharing more about our mission and products during the interview.
The Role
As a Senior ML Engineer specializing in Advertising Intelligence, you will lead the development of our machine learning systems that extract insights from vast amounts of advertising data. You'll build models that identify patterns, predict outcomes, and generate recommendations that help our clients maximize their advertising ROI. This role sits at the intersection of machine learning engineering and advertising domain expertise, requiring both technical depth and business acumen. You'll work closely with our data engineering and product teams to translate business problems into ML solutions, rapidly prototype and test new approaches, and scale successful models to production. This is an opportunity to shape how AI and ML transform the advertising industry.Key Responsibilities
Design, develop, and deploy machine learning models that extract actionable insights from advertising performance data
Build and optimize systems that leverage LLMs to generate natural explanations of advertising trends and recommendations
Create clustering and classification models to segment audiences, campaigns, and creative assets based on performance characteristics
Develop predictive models for forecasting and optimizing ad performance, budget pacing, and ROI
Collaborate with other engineers to design efficient data pipelines that feed our ML systems
Work with product managers to translate customer needs into ML-powered features
Requirements
5+ years of experience in applied machine learning
Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
Proven experience building and deploying ML models in production environments
Hands-on experience with various ML techniques including classification, regression, clustering, and time series analysis
Solid understanding of statistical analysis and experimental design
Familiarity with LLMs and their application in business intelligence use cases
Experience with data visualization and BI tools to communicate ML insights
Strong software engineering practices including version control, testing, and CI/CDExcellent communication skills to explain complex ML concepts to non-technical stakeholders
Bachelor's degree in Computer Science, Statistics, Mathematics, or related field (advanced degree )
Qualifications
Experience working with advertising data or in AdTech companies
Knowledge of major advertising platforms (Meta, Google Ads, Amazon, TikTok) and their metrics
Experience with recommendation systems and personalization algorithms
Familiarity with marketing attribution models and customer journey analytics
Hands-on experience fine-tuning and prompting LLMs for specific business domains
Experience working with large datasets and distributed computing frameworks (e.g., Spark)
Experience with MLOps tools and practices for model monitoring and management
Knowledge of privacy-preserving ML techniques and regulations related to digital advertising (GDPR, CCPA)
What We Offer
Competitive salary, stock, and benefits package
Opportunity to shape the ML strategy of a growing startup from the ground up
Work on challenging problems at the intersection of machine learning and digital advertising
A collaborative, inclusive, and dynamic work environment in a high-growth start-up
Work with a set of industry veterans that have 15+ years experience from early start-ups to the biggest tech companies
Regular opportunities to learn and grow through tech talks, conferences, and continued education
We are an equal-opportunity employer and value and at our company.
Benefits include employee stock options and medical/dental/vision insurance.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Design, develop, and deploy machine learning models that extract actionable insights from advertising performance data
Build and optimize systems that leverage LLMs to generate natural explanations of advertising trends and recommendations
Create clustering and classification models to segment audiences, campaigns, and creative assets based on performance characteristics
Develop predictive models for forecasting and optimizing ad performance, budget pacing, and ROI
Collaborate with other engineers to design efficient data pipelines that feed our ML systems
Work with product managers to translate customer needs into ML-powered features
Requirements
5+ years of experience in applied machine learning
Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
Proven experience building and deploying ML models in production environments
Hands-on experience with various ML techniques including classification, regression, clustering, and time series analysis
Solid understanding of statistical analysis and experimental design
Familiarity with LLMs and their application in business intelligence use cases
Experience with data visualization and BI tools to communicate ML insights
Strong software engineering practices including version control, testing, and CI/CDExcellent communication skills to explain complex ML concepts to non-technical stakeholders
Bachelor's degree in Computer Science, Statistics, Mathematics, or related field (advanced degree )
Qualifications
Experience working with advertising data or in AdTech companies
Knowledge of major advertising platforms (Meta, Google Ads, Amazon, TikTok) and their metrics
Experience with recommendation systems and personalization algorithms
Familiarity with marketing attribution models and customer journey analytics
Hands-on experience fine-tuning and prompting LLMs for specific business domains
Experience working with large datasets and distributed computing frameworks (e.g., Spark)
Experience with MLOps tools and practices for model monitoring and management
Knowledge of privacy-preserving ML techniques and regulations related to digital advertising (GDPR, CCPA)
What We Offer
Competitive salary, stock, and benefits package
Opportunity to shape the ML strategy of a growing startup from the ground up
Work on challenging problems at the intersection of machine learning and digital advertising
A collaborative, inclusive, and dynamic work environment in a high-growth start-up
Work with a set of industry veterans that have 15+ years experience from early start-ups to the biggest tech companies
Regular opportunities to learn and grow through tech talks, conferences, and continued education
We are an equal-opportunity employer and value and at our company.
Benefits include employee stock options and medical/dental/vision insurance.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.