ML Engineer - Recommender & Personalization (Remote)

7Seventy; United States; Teletrabalho; USD 180 000 - 275 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health, dental, and vision insurance

401(k) retirement plan with company匹配

Unlimited paid time off

Generous parental leave policy

Equity participation with potential金融起

Resumo da oferta

7Seventy is seeking a Machine Learning Engineer - Applied / Product to build scalable ML-powered applications using behavioral foundation models. The role focuses on developing ML models, metrics, pipelines, systems, and services that support production applications, personal experiences, and data-driven decisions.

Ground-up product development is a significant part of this role. This position blends hands-on ML engineering with product development and experimentation.

Qualificações

• Hands-on experience with consumer-facing ML applications or problems (e.g., recommender systems or personalization).
• Ability to explain technical contributions and their impact.
• Experience linking ML engineering workflows across models, data pipelines, infrastructure, and application development.

Responsabilidades

• Develop and improve ML models, metrics, pipelines, systems, and services powering ML-driven apps.
• Build ML-powered products for personalization and decision-making.
• Contribute to end-to-end ML application development and product implementation.
• Develop new capabilities and systems from the ground up with ownership of substantial engineering work.
• Collaborate with Product teams and ML engineers to translate signals into practical applications.

Ferramentas

Airflow

Bazel

GitHub CI/CD

Spark

Descrição da oferta de emprego

7Seventy is seeking a Machine Learning Engineer - Applied / Product to build scalable ML-powered applications using behavioral foundation models. The role focuses on developing ML models, metrics, pipelines, systems, and services that support production applications, personal experiences, and data-driven decisions.

Ground-up product development is a significant part of this role. This position blends hands-on ML engineering with product development and experimentation.