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Sr. Staff Machine Learning Engineer in United States at Jobgether

NewJob Function: Information Technology
Jobgether
United States, United States
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Job Description

Sr. Staff Machine Learning Engineer

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

This senior-level role sits at the core of a fast-scaling fintech environment, where machine learning directly shapes product performance, risk intelligence, and customer experience. You will lead the end-to-end design and deployment of production-grade ML systems that operate at scale and deliver measurable business impact. The role blends deep technical ownership with cross-functional collaboration across data science, product, and engineering teams. You will work on high-impact problems such as prediction modeling, optimization, and large-scale data processing in a cloud-native environment. With significant autonomy, you will define best practices for ML system design, monitoring, and lifecycle management. This is a hands-on leadership role ideal for someone who thrives in building robust, scalable systems in dynamic, data-rich environments.

Accountabilities:
  • Own the end-to-end lifecycle of machine learning systems, including data ingestion, preprocessing, model training, deployment, monitoring, and ongoing optimization in production environments.
  • Design and maintain scalable and reliable data pipelines supporting large-scale model training and inference workflows.
  • Develop, implement, and optimize machine learning models that meet performance, latency, scalability, and business requirements.
  • Partner with data scientists, product managers, and engineers to translate product goals into production-ready ML solutions.
  • Continuously evaluate and improve model performance through experimentation, hyperparameter tuning, and monitoring of real-world outcomes.
  • Leverage distributed systems and cloud infrastructure to process and analyze large-scale datasets efficiently.
  • Stay current with advancements in machine learning, MLOps, and production engineering practices to continuously enhance system capabilities.
  • Apply domain expertise (e.g., payments risk, fraud detection, or customer success) and NLP approaches where relevant to improve product intelligence.
Requirements
  • Master’s or Ph.D. in Computer Science, Engineering, or a related technical field.
  • 6+ years of experience building and deploying machine learning systems in production environments.
  • Strong programming skills in Python and hands-on experience with ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
  • Proven experience designing end-to-end ML pipelines, including data processing, model training, deployment, and monitoring.
  • Strong background in cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure.
  • Experience with distributed computing frameworks like Apache Spark and orchestration tools such as Kubernetes.
  • Strong knowledge of model optimization, CI/CD practices, version control, and MLOps principles.
  • Excellent analytical thinking, problem-solving skills, and ability to collaborate across cross-functional teams.
  • Exposure to NLP models and/or fraud, risk, or fintech-related ML domains is a strong plus.
Benefits
  • Competitive compensation package aligned with market benchmarks and experience level.
  • Company equity enabling participation in long-term organizational growth.
  • Comprehensive medical, dental, and vision insurance coverage.
  • 401(k) retirement savings plan with employer match (for U.S.-based employees).
  • Unlimited paid time off plus company holidays.
  • Parental leave and family-supportive policies.
  • Flexible remote-friendly work environment with occasional in-person onboarding and collaboration sessions.
  • Access to modern ML infrastructure, cloud platforms, and continuous learning opportunities.
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!
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.
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Job Location

United States, United States

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