Senior ML Engineer
Listed on 2026-03-16
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IT/Tech
Machine Learning/ ML Engineer, AI Engineer
Job Description
We are hiring a Senior ML Engineer to build, deploy, and support machine learning models and optimization systems on AWS. This role sits between data science and platform engineering, turning models into reliable production services and batch pipelines. The ideal candidate has deep experience with MLOps, APIs, cloud-native deployment, model serving, workflow orchestration, and enterprise-scale ML platforms.
Responsibilities- Productionize machine learning and optimization models as scalable APIs, batch jobs, and event-driven services.
- Build and maintain ML deployment pipelines on AWS using container, serverless, and Kubernetes-based patterns.
- Partner with data scientists to integrate models into enterprise applications and operational systems.
- Design model inference services, batch scoring pipelines, and orchestration layers for real-time and offline use cases.
- Implement model monitoring, validation, drift detection, and post-deployment support processes.
- Build robust data ingestion and feature pipelines using streaming and batch architectures.
- Create reusable ML service frameworks, deployment templates, and CI/CD workflows.
- Improve model reliability, latency, and cost efficiency in production.
- Support experimentation, tooling evaluation, and platform decisions for ML lifecycle management.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- 7+ years in software engineering or platform engineering, with 3+ years in ML engineering or MLOps.
- Strong experience deploying ML models to production on AWS.
- Hands-on experience with AWS services such as Sage Maker, ECS, EKS, Lambda, Athena, S3, SQS, SNS, and CDK/Cloud Formation/Terraform.
- Strong Python skills and working knowledge of Java, Scala, or Go.
- Experience with ML frameworks and tools such as scikit-learn, Tensor Flow, XGBoost, FastAPI, Airflow, Spark, and Jupyter.
- Experience building REST APIs around models for enterprise consumption.
- Experience with Kubernetes, CI/CD pipelines, infrastructure as code, and monitoring.
- Strong background in distributed systems, microservices, and cloud-native architecture.
- Experience serving models in real-time and batch settings at enterprise scale.
- Experience with NLP, optimization models, forecasting, classification, or fraud and identity models.
- Experience with Red Hat Open Shift or Kubernetes-based ML deployments.
- Experience with data lakes, Spark, Parquet, streaming ingestion, and large-scale analytics platforms.
- Exposure to multi-cloud environments including AWS, GCP, and Azure.
- Ability to mentor engineers and drive architecture standards.
- ML models reliably deployed and maintained in production.
- Faster cycle time from model development to business impact.
- Strong operational excellence around monitoring, validation, and support.
- Scalable ML platform patterns that can be reused across teams.
Momentive Software amplifies the impact of over 20,000 purpose-driven organizations in over 30 countries, with over $11 billion raised and 55 million members served to date. Mission-driven nonprofits and associations rely on Momentive’s cloud-based software and services to address their most pressing challenges – from engaging their communities to simplifying operations and growing revenue. Momentive partners with organizations that believe "good enough" is never enough – so they can bring on better outcomes for everyone they serve.
Learn more at
At Momentive Software, we’re a team of passionate problem-solvers, innovators, and volunteers who believe in using technology to make a real difference. We dream big, support each other, and take pride in creating solutions that help our customers drive meaningful change. If you’re looking for a place where your work matters and your ideas are valued, you’ll find it here.
- Medical, Dental & Vision Benefits
- 401(k) Savings Plan with Company Match
- Flexible Planned Paid Time Off
- Generous Sick Leave
- Inclusive & Welcoming Environment
- Purpose-Driven Culture
- Work-Life Balance
- Commitment to Community Involvement
- Employer-Paid Parental Leave
- Employer-Paid Short-Term…
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