Senior Machine Learning Engineer (AI)

Location: Remote or offices in Seattle, San Francisco, or Mountain View, United States. hirify.global can hire in any country where it has a legal entity.

Salary: United States base pay ranges from $171,063 to $223,332 in Zone C, $185,490 to $242,168 in Zone B, and $206,100 to $269,075 in Zone A, plus possible benefits, bonuses, commissions, and equity.

Company

hirify.global develops software products that help teams collaborate and manage different types of work.

What you will do

• Lead the design, development, deployment, and continuous improvement of production machine learning systems.
• Build intelligent search, recommendations, conversational experiences, and other AI capabilities.
• Develop scalable data and modeling approaches for large and complex datasets.
• Design architectures that meet quality, latency, scale, reliability, privacy, and cost requirements.
• Run experiments, offline evaluations, online tests, and error analyses to measure model and product impact.
• Collaborate with product, engineering, data science, analytics, and platform teams while mentoring other machine learning engineers.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.
• At least 5 years of professional experience developing and deploying machine learning or data science solutions in production.
• Strong programming skills in Python and at least one production language such as Java, Kotlin, or TypeScript.
• Strong SQL knowledge and experience with large-scale data processing technologies such as Spark.
• Experience designing, training, evaluating, deploying, and scaling machine learning models using large and complex datasets.
• Experience with cloud-based data and machine learning environments such as AWS or Databricks, plus strong communication and problem-solving skills.

Nice to have

• Experience with search, recommendation, ranking, personalization, NLP, deep learning, or large language models.
• Experience with agentic systems, tool-using models, multi-step reasoning, or planning systems.
• Experience with ML platforms, model serving, feature stores, data pipelines, observability, or responsible AI.
• Technical leadership experience, including influencing architecture and mentoring engineers.

Culture & Benefits

• Flexible remote, office, or hybrid work options.
• Health and wellbeing resources.
• Paid volunteer days.
• Benefits may include bonuses, commissions, and equity.
• Inclusive collaboration, continuous learning, experimentation, and iterative delivery are encouraged.

Hiring process

• Recruitment support and accommodations are available throughout the hiring process.
• Identity verification may be required as a condition of employment.