Senior Machine Learning Engineer

Job Description

• 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.
• Accountabilities: 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.
• How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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