Staff Machine Learning Engineer (Offsite Ads)

Location: Mountain View, USA

Base pay: $164K–$282K per year; annual bonus of 0–20% of base salary.

Company

hirify.global is a large global public e-commerce company building commerce and advertising products, including an offsite advertising platform that connects advertisers with customers across the open internet.

What you will do

• Design and build machine learning models and systems for ad targeting, ranking, bidding, and campaign performance.
• Develop large-scale prediction and optimization models, including CTR, CVR, GMV, and bidding optimization.
• Apply LLMs, embeddings, agentic AI, deep learning, and related technologies to advertising problems.
• Build scalable ML infrastructure and production systems for experimentation and reliable model deployment.
• Define success metrics, evaluate business impact, and improve models through data-driven experimentation.
• Partner with Product, Engineering, Data Science, and business teams; own initiatives through production and mentor engineers.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related quantitative field.
• 6+ years of industry experience developing and deploying machine learning solutions in production environments.
• Strong foundation in machine learning, deep learning, statistical modeling, optimization, and large-scale data systems.
• Production-grade ML development experience using Python and/or Java.
• Strong PyTorch experience and modern deep learning architectures for prediction, ranking, recommendation, retrieval, or optimization.
• Ability to solve complex and ambiguous business problems through data-driven analysis and ML innovation.
• Track record of owning large technical initiatives and delivering measurable business impact.

Nice to have

• Master’s degree or PhD in a relevant technical or quantitative field.
• Experience in digital advertising, recommendation systems, ranking systems, marketplace optimization, or large-scale machine learning.
• Experience with LLMs, generative AI, embedding models, retrieval systems, or agentic AI.
• Experience with distributed training, model serving, and cloud ML platforms.
• Familiarity with XGBoost, LightGBM, Scikit-learn, MLflow, Kubeflow, Spark, and Airflow.
• Strong communication and collaboration skills, technical strategy experience, and comfort in a fast-paced, high-growth environment.

Culture & Benefits

• Startup culture with the resources of a large global public company and opportunities to drive new initiatives.
• Medical, dental, vision, life, AD&D, disability, FSA, and HSA benefits.
• 401(k) plan with company match, 18–21 days of PTO based on tenure, 12 public holidays, and six weeks of paid parental leave.
• Pre-tax commuter benefits and free electric car charging at the Mountain View location.
• Employee Assistance Program and additional workplace support.

Hiring process

• Application review, phone interview, onsite or virtual onsite interview, and offer.
• The process may vary by role and scheduling circumstances; interview updates are sent to the submitted email address.