Sr. Machine Learning Engineer

Job Description

• This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Sr. Machine Learning Engineer in the United States. This is a high-impact engineering role at the intersection of machine learning, data infrastructure, and large-scale production systems. You will be responsible for designing and owning the core ML infrastructure that powers data-driven decision-making across millions of daily user interactions. Working closely with data scientists, data engineers, and product teams, you will transform experimental models into scalable, production-grade systems. The role requires deep technical expertise in building robust ML pipelines, feature stores, and cloud-native architectures. You will play a critical role in shaping the future of the data platform, ensuring reliability, scalability, and performance of machine learning systems in production. This position is ideal for a hands-on engineer who thrives in complex, high-scale environments and enjoys bridging research and production engineering.
• Accountabilities: Architect and own the end-to-end machine learning infrastructure, ensuring scalable and production-ready systems. Partner with data science teams to productionize models and transition algorithms from research to real-world applications. Design, build, and maintain feature stores (offline and online) to support real-time and batch model inference. Develop and optimize ML pipelines and data workflows using modern cloud-native architectures. Collaborate with data engineering teams to enhance data lake, ETL, and streaming data infrastructure. Lead system monitoring, observability, and performance optimization for production ML models. Contribute to architectural decisions and define best practices for scalable data and ML systems. Ensure reliability, fault tolerance, and efficiency across all machine learning services in production. Support cross-functional collaboration by translating data science needs into scalable engineering solutions. Requirements: 5+ years of experience in Machine Learning Engineering, with strong focus on production systems and data engineering. Strong expertise in AWS cloud services (e.g., SageMaker, DynamoDB) and infrastructure-as-code tools such as Terraform, CDK, or CloudFormation. Deep experience with containerization and orchestration technologies including Docker and Kubernetes. Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Advanced knowledge of ETL pipelines, database systems, and large-scale data processing. Experience with big data and distributed systems such as Snowflake, Databricks, or Kafka is highly desirable. Strong understanding of SQL and data modeling for analytical and operational use cases. Proven ability to collaborate across data science, engineering, and product teams. Strong problem-solving skills with a focus on scalability, reliability, and performance. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience). Benefits: Competitive annual salary ranging from $164,000 to $194,000 Fully remote work setup with all necessary tools and equipment provided Unlimited paid time off (PTO) for flexibility and work-life balance Comprehensive medical, dental, and vision insurance coverage 401(k) retirement plan through Charles Schwab Health Savings Account (HSA), Flexible Spending Account (FSA), and Limited FSA options Company-paid short-term and long-term disability insurance and basic life insurance Paid parental leave for maternity and paternity support Employee Assistance Program (EAP) offering mental health, legal, and financial support services Wellness benefits including access to a wellness coaching app for employees and family members Employee discount program with savings across travel, retail, and services Paid volunteer time off to support community engagement
• 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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