SS&C Technologies Logo

SS&C Technologies

Principal ML Engineer

Reposted 11 Days Ago
Be an Early Applicant
In-Office
City Point, City of Boston, MA, USA
Senior level
In-Office
City Point, City of Boston, MA, USA
Senior level
Design and build machine learning platforms and pipelines, lead model lifecycle infrastructure development, and mentor junior members while promoting best practices in ML operations.
The summary above was generated by AI

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 infrastructure, CI/CD pipelines, and automated ML workflows to support continuous delivery.
  • Lead methodology improvements, drive technical standards, and mentor junior engineers across data and ML engineering teams.
  • Provide production support and ensure site reliability for deployed ML systems, including proactive monitoring, alerting, and incident response to minimize downtime and performance degradation.
  • Own escalation workflows for production incidents — triage issues, coordinate resolution across teams, conduct root cause analysis, and implement preventive measures to improve system stability.

Required Experience

  • 8+ years of relevant experience in data engineering, ML engineering, or a related field, with a Bachelor’s degree in Computer Science or a quantitative discipline.
  • Strong Python programming skills with hands-on experience using frameworks such as Flask, Django, FastAPI, or Celery.
  • Solid experience with ML SDLC, microservices architecture, and productionizing Python or Java applications.
  • Hands-on experience with AWS (EC2, S3, Data Lake), Kubernetes, and CI/CD tooling including Jenkins, Terraform, Splunk, and Grafana.
  • Familiarity with ML frameworks (PyTorch, Keras, scikit-learn) and experience building end-to-end data and ML pipelines.
  • Proven experience with RESTful API development, containerized deployments (Docker/Kubernetes), and delivering scalable ML models in production.
  • Linux proficiency, strong software engineering fundamentals, and experience with databases including MongoDB, PostgreSQL, Milvus, Chroma, and Pinecone.

What Sets You Apart (preferred qualifications)

  • Master’s degree in Computer Science, Data Science, or a related quantitative field.
  • Experience with big data and ML orchestration tools such as Spark, Dask, Kubeflow, or Airflow.
  • Familiarity with additional cloud platforms (GCP, Azure) and data warehousing solutions such as Snowflake.
  • Prior experience designing microservices architectures and working with distributed systems at enterprise scale.

Join SS&C, where innovation meets global opportunities. Click here to apply.

#LI-PE1

#LI-HYBRID



Unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.



SS&C Technologies offers a comprehensive total rewards package designed to support your wellbeing, growth, and future. Our benefits include medical, dental, and vision coverage; a 401(k) plan with company match; paid time off, holidays, and parental leave; and professional development reimbursement opportunity.

Actual base salary will vary based on several factors, including but not limited to relevant skills, prior experience, education, demonstrated performance, and geographic location.

Massachusetts: The expected base salary for the position is between 150,000 USD to 160,000 USD.

 


Applications will be accepted on an ongoing basis until the position is filled.



SS&C Technologies is an Equal Employment Opportunity employer and does not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.

SS&C Technologies Boston, Massachusetts, USA Office

50 Milk St, Boston, MA, United States, 02110

Similar Jobs

14 Days Ago
Remote or Hybrid
United States
184K-310K Annually
Expert/Leader
184K-310K Annually
Expert/Leader
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Lead the design, development, and deployment of foundational ML systems, influence architecture, mentor engineers, and drive strategic initiatives within SailPoint's AI team.
Top Skills: AirflowAWSBedrockCloudbeesDbtFeastJavaJenkinsKafkaPythonRustSagemakerShell/BashSnowflakeSQL
2 Days Ago
Remote or Hybrid
USA
75K-404K Annually
Expert/Leader
75K-404K Annually
Expert/Leader
Consumer Web • Coupons • Healthtech • Social Impact • Pharmaceutical
Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.
Top Skills: AirflowAWSAzureGCPGoPythonPyTorchTensorFlowXgboost
6 Hours Ago
Easy Apply
Remote or Hybrid
14 Locations
Easy Apply
150K-200K Annually
Senior level
150K-200K Annually
Senior level
Automotive • Big Data • Insurance • Software • Transportation
The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.
Top Skills: AirflowAWSAzureGCPPythonPyTorchSagemakerSQLXgboost

What you need to know about the Boston Tech Scene

Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.

Key Facts About Boston Tech

  • Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
  • Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
  • Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
  • Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account