Senior Machine Learning Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer in United States.

This role sits at the heart of a fast-evolving platform powering the creator and affiliate economy through intelligent commerce and mobile-first innovation. You will be responsible for building and scaling end-to-end machine learning systems that directly influence product decisions, user experiences, and monetization strategies. Working across data, product, and engineering teams, you will transform ambiguous business challenges into production-grade ML solutions. The environment is highly collaborative and experimentation-driven, requiring strong ownership from data ingestion through deployment and monitoring. You will design scalable pipelines, robust feature systems, and efficient inference services that support real-time and batch decisioning. This is a high-impact opportunity to shape how machine learning drives growth, personalization, and performance at scale.

• Own the full machine learning lifecycle, including feature engineering, data pipelines, model training, deployment, monitoring, and retraining in production environments.
• Design and build scalable, reliable data and feature pipelines, including feature store patterns ensuring consistency across training and inference workflows.
• Develop and optimize ML models for ranking, recommendation, classification, regression, and decisioning use cases.
• Implement and maintain batch scoring pipelines and real-time inference services with strong standards for latency, reliability, and performance.
• Collaborate with data scientists to operationalize models and build experimentation frameworks for evaluation and iteration.
• Partner with software engineers to integrate ML models into production systems, APIs, and customer-facing applications.
• Establish observability and monitoring for ML systems, including data drift, feature quality, model performance, and system health.
• Support rapid experimentation and safe deployment strategies for new models and iterations.
• Contribute to architecture design, technical documentation, and best practices for ML engineering across teams.
• Mentor peers through code reviews, technical discussions, and design guidance while contributing to platform-wide ML decisioning systems.

Requirements:

• 5+ years of professional experience in machine learning engineering, software engineering, or data engineering roles.
• Strong proficiency in Python and SQL with hands-on experience building production systems.
• Proven track record of designing, building, and operating large-scale data and ML pipelines.
• Experience deploying and maintaining machine learning models in production environments.
• Solid understanding of the full ML lifecycle, including feature generation, training, deployment, and monitoring.
• Experience with cloud environments, particularly AWS.
• Familiarity with orchestration and data tools such as Airflow, dbt, or similar frameworks.
• Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Strong software engineering practices including testing, debugging, documentation, and system design.
• Experience with feature pipelines or feature store architectures supporting training and online inference.
• Exposure to ranking, recommendation, or decisioning systems is a strong plus.
• Ability to work effectively in ambiguous environments and translate product needs into ML solutions.

Benefits:

• Competitive salary range: $153,000–$198,000 depending on experience and qualifications.
• Remote-first “RemotePlus” model with access to in-person collaboration hubs in New York City.
• 401(k) plan with automatic 3% employer contribution.
• Comprehensive health, dental, and vision insurance, with full employer coverage for many employee plans and partial coverage for dependents.
• Unlimited paid time off, including birthdays off, and company-wide mental health weeks.
• Employee Assistance Program and wellness support resources.
• Monthly mobile phone and internet stipend, plus annual lifestyle stipend.
• Complimentary One Medical memberships for employees and dependents.
• Access to WeWork memberships in select locations and regular coworking and social events.
• Inclusive and flexible culture focused on learning, experimentation, and delivery.