Ss&c

Financial Services, Healthcare Technology

PrincipalMLEngineer

$150–160k Waltham, Massachusetts, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Principal ML Engineer at Ss&c. Skills: ML Engineering, MLOps, Cloud-native ML, Platform development. Build scalable ML deployment pipelines. Design cloud-native ML workflows”

Industry & Context.

Financial Services, Healthcare Technology
Problems you'll solve

Root cause analysis

What They're Looking For.

Must Have

8+ years relevant experience, Bachelor's degree in Computer Science, Python programming skills, Flask, Django, FastAPI, or Celery experience, ML SDLC experience, Microservices architecture experience, Productionizing Python or Java applications, AWS (EC2, S3, Data Lake) experience, Kubernetes experience, CI/CD tooling experience, Jenkins, Terraform, Splunk, Grafana experience, ML frameworks (PyTorch, Keras, scikit-learn) experience, End-to-end data and ML pipelines experience, RESTful API development experience, Containerized deployments (Docker/Kubernetes) experience, Scalable ML models in production experience, Linux proficiency, Software engineering fundamentals, MongoDB, PostgreSQL, Milvus, Chroma, Pinecone experience

Nice to Have

Master's degree in Computer Science, Big data and ML orchestration tools experience, Spark, Dask, Kubeflow, or Airflow experience, GCP, Azure experience, Snowflake experience, Microservices architectures design experience, Distributed systems at enterprise scale experience

What You'll Do.

Build scalable ML deployment pipelines

Design cloud-native ML workflows

Develop tooling for ML lifecycle

Create RESTful APIs for model management

Operationalize ML solutions

Bridge research and production gap

Design deployment infrastructure

Maintain CI/CD pipelines

Automate ML workflows

Support continuous delivery

Lead methodology improvements

Drive technical standards

Mentor junior engineers

Provide production support

Ensure site reliability for ML systems

Minimize downtime and performance degradation

Own escalation workflows for incidents

Triage production issues

Coordinate incident resolution

Conduct root cause analysis

Implement preventive measures

How You'll Work.

Team & Collaboration

Partner with Data Scientists; Partner with Engineers; Mentor junior engineers

Process & Methodology

CI/CD

Full Job Description

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology. **_Job Description_** Principal ML Engineer **Locations:** Waltham, MA (Hybrid) **About the Role** We are looking for a Principal ML Engineer to design, build, and operationalize machine learning platforms and pipelines that power real business outcomes. In this senior role, you will lead the development of model lifecycle infrastructure, cloud-native ML workflows, and automated deployment processes — while mentoring junior engineers and championing ML engineering best practices across the organization. **Why Join SS &C ** SS&C combines proprietary technology with deep industry expertise to support complex financial and health care operations. Our teams design, implement, and operate solutions that help clients manage data, automate processes, and scale their businesses with confidence. You will work with industry experts, modern platforms, and evolving technologies, gaining exposure to real-world operational challenges and large-scale enterprise environments. **How You Will Make an Impact** * Build scalable, self-service ML model deployment pipelines that enable teams to move from experimentation to production with speed and reliability. * Design cloud-native ML workflows aligned with organizational strategy and modern MLOps principles. * Develop tooling for model development, deployment, monitoring, and reporting across the full ML lifecycle. * Create and maintain RESTful APIs for model lifecycle management, ensuring scalability, security, and reliability. * Partner with Data Scientists and Engineers to operationalize ML solutions and bridge the gap between research and production. * Design and maintain deployment infr

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