4 model serving engineer jobs at 4 companies in Fall River, MA
🚀PromotedHiringCafe
ML Engineer - Inference & Model Deployment
Cupertino, CA, US
$250k-$310k/yrOn-SiteFull Time
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Turn powerful AI and ML models into fast, reliable production systems. Own inference latency, throughput, model-serving architecture, multi-GPU systems, and production deployment for millions of users.
Fidelity Investments: Provides investment management, retirement planning, and brokerage services.
3+ YOEBachelor's (or Master's) in CS/Engineering/IT/Data Science/Analytics/Mathematical Finance and 5 (or 3 with Master's) years' relevant experience; expertise in AWS, Python, ML infra, RAG systems, vector DBs, and production model serving.
New York or Chicago or Boston or Toronto or London
$130k-$147k/yrHybridFull Time
Curinos: Providing data-driven decision intelligence for global financial institutions.
Experience operationalizing production ML/AI on Databricks, MLflow, Databricks Model Serving; strong Python, Spark, SQL; CI/CD and monitoring for model performance, safety, and governance.
Databricks, Databricks Workflows, Delta Lake, Delta Live Tables, Asset Bundles, Unity Catalog, Genie Code, MonteCarlo, Fiddler, MLflow, Databricks Model Serving, Python, Spark, SQL, Jenkins, shell, Yarn, AWS, chatGPT, Claude, Copilot
Glia AI: Automated AI systems engineering for high-performance infrastructure.
Proven engineering leader with hands-on systems and software expertise across model serving, distributed systems, and AI workloads; strong Python and PyTorch skills; experience managing small, high-performance teams.
United States or Canada or San Francisco or New York City or Seattle or Boston or Chicago or Denver or Austin or Portland
$195k-$358k/yrRemoteFull Time
Outschool: Marketplace for live online small-group classes for children.
10+ YOE5+ Mgmt10+ years in data/analytics/engineering roles, 5+ years managing data or analytics teams, strong SQL/dbt/data modeling skills, experience with Redshift, self-serve analytics tools, experimentation, and stakeholder communication.