Staff Machine Learning Engineer (Ads Ranking)

Location: Mountain View, USA

Base pay: $164,000–$282,000 per year, depending on geographic market, knowledge, skills, and experience.

Company

hirify.global is a large global public commerce company with a startup culture, building shopping, eating, and living services and operating advertising products within its e-commerce marketplace.

What you will do

• Architect, build, and deploy large-scale machine learning and deep learning models for ad targeting, relevance, ranking, and user engagement.
• Develop automated bidding, query expansion, and advertiser ROI optimization algorithms.
• Design marketplace intelligence systems that provide actionable growth insights to advertisers.
• Architect and evolve end-to-end ML infrastructure for high-throughput, low-latency ad requests at internet scale, supporting over 1 billion daily ad impressions.
• Lead technical projects across multiple engineering teams and align roadmaps with business objectives.
• Mentor mid-level and senior engineers and collaborate with Product Management, Data Science, and Business Leadership.

Requirements

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics, or a closely related field.
• At least 4 years of professional experience in applied machine learning.
• Experience with machine learning, deep learning, and statistical modeling.
• Proficiency in Python and/or Java, with experience building production-grade ML systems.

Nice to have

• Master’s or PhD in a relevant technical field.
• Experience with search systems, information retrieval, or recommendation engines.
• Experience with LLMs, embeddings, and vector search technologies.
• Experience with AWS or Google Cloud Platform, including Vertex AI, BigQuery, or SageMaker.
• Startup or high-growth environment experience and the ability to lead cross-functional teams in a multicultural, global organization.
• Hands-on experience with TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM, or H2O.ai.
• Experience with MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker.
• Excellent communication skills, including explaining complex technical concepts to technical and non-technical stakeholders.
• Ability to work independently and manage ambiguity in fast-paced environments.

Culture & Benefits

• Startup culture supported by the resources of a large global public company.
• Annual bonus of 0–20% of base salary, plus potential equity and other compensation.
• Medical, dental, vision, life, AD&D, disability, employee assistance, FSA, and HSA benefits.
• 401(k) plan with company match, 18–21 days of paid time off based on tenure, 12 paid holidays, and paid parental leave.
• Pre-tax commuter benefits and a free electric car charging station in Mountain View.

Hiring process

• Application review, job fit interview, focus interview, and offer.
• The process and schedule may vary; results and interview details are communicated by email.
• The posting may close early if all openings are filled, and offers may be rescinded for false application information.