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This position as a Principal ML Engineer at Agero involves architecting and shipping end-to-end Python services for dispatch purposes. The role also entails building ML models and horizon simulations, as well as automating training, validation, A/B rollout, and monitoring processes. The ideal candidate will lead and collaborate with ML engineers, mentor them, and align with product, operations, and executives. Continuously improving by instrumenting telemetry and identifying failure modes is a key aspect of this role.
Requirements include at least 6 years of experience in ML Engineering with production ownership, expertise in Python, optimization skills in MILP/LP/Stochastic and ML technologies like XGBoost and PyTorch. Cloud-native pipeline experience on AWS, GCP, or Azure is crucial. Proficiency in SQL, feature-store design, and a data-quality mindset are also desired. Dispatch/logistics experience is a plus. Agero offers an inclusive, growth-minded culture with various benefits such as health, dental, vision, disability, life insurance, 401(k) with company match, tuition assistance, flexible time off, paid sick leave, ten holidays, and parental planning benefits.
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Design and implement ArcGIS platform-based strategies
Define business continuity for on-prem and cloud deployments with security and governance
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Enable simulation for planning, development, and operations
Develop high-fidelity simulation of spacecraft hardware/software
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Develop reliable payment solutions
Implement AI to enhance payment success and reduce fraud
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Design robust, scalable, secure database solutions
Collaborate with cross-functional teams
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Deploy and optimize ArcGIS deployments
Migrate content between ArcGIS deployments
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Lead automation build-out for datacenter servers
Manage end-to-end machine lifecycle
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Design and implement an AI evaluation framework with defined metrics
Build reusable agent infrastructure for multi-turn workflows
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Lead strategic technical discussions with customers
Design and implement robust, scalable, secure DB solutions
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Collaborate with ML and full-stack teams on document mining challenges
Scale data pipelines efficiently
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Deploy and configure ArcGIS in various environments
Migrate content between ArcGIS deployments
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Design and implement ArcGIS platform-based strategies to meet customer needs
Define business continuity for on-prem and cloud deployments
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Develop and deploy predictive models for fraud prevention.
Collaborate with cross-functional teams for real-time solutions.
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Lead application security direction and design frameworks
Architect and automate security controls at scale
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Deploy and configure ArcGIS across diverse platforms
Plan and execute content migrations between ArcGIS deployments
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Set technical strategy and collaborate with cross-functional teams
Define technical solutions and operational processes
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Set technical vision and strategy
Lead engineering team
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Support product squads and collaborate with various teams
Measure impact and present findings
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Architect and implement data pipelines
Integrate and normalize data sources
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Deploy and configure ArcGIS in diverse environments
Migrate content between ArcGIS deployments across architectures
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Develop AI-powered backend APIs and frontend interfaces.
Mentor peers and lead AI/ML integration efforts.
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Design, build, and maintain backend services powering GoDaddy’s backup infra
Develop RESTful APIs integrating across hosting platforms
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Design and implement abuse detection techniques
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Architect and build cutting-edge Conversational AI products
Lead and mentor engineering teams
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Guide customers through product implementation and support
Build custom demos and prototypes for customer use cases
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Improve AI systems through code validation, refinement, and benchmarking
Provide structured feedback on solution quality and clarity
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Develop and maintain backend systems using Python.
Utilize cloud services like GCP, AWS, and Azure.
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Build and refine data infrastructure and tools
Collaborate with teams to integrate systems
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Leading and mentoring a team in Hardware/EEE Reliability
Conducting failure analysis and mitigation
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Design, code, and maintain secure asset solutions
Enhance smart contract security programs
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Execute commercial strategy and analyses for FanDuel Predicts
Own performance tracking and strategic analyses for the product
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Develop and maintain backend platform for mortgage lenders
Own features from design to production release
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Optimizing product performance through data analysis
Collaborating with key stakeholders for product decisions
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Lead identity security initiatives
Implement and improve IAM systems
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Code, test, debug, and maintain production software for features
Collaborate with cross-functional teams to ensure smooth releases
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Design and develop custom automation solutions
Commission, deploy, and maintain automation tools
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Architect, build, and optimize payments platform
Collaborate with cross-functional teams
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Provide IT support for SF office and escalate complex issues globally
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Owning the quality of new features through planning tests and providing feedback
Defining test strategies for P0 launches
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Architect and improve detection capabilities
Enhance detection strategy with new detections
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Develop and scale network operations processes and tools
Analyze operations data for efficiency improvements
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Serve as technical and strategic advisor to partners on payroll solutions
Collaborate with sales in pre-sales to design holistic solutions
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Deliver high-impact software projects
Collaborate with engineers and partners
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Plan and scale technology projects
Lead data architecture, security, and performance
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Leading a team at the product engineering and delivery intersection
Developing tooling and automation for repeatable deployments
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Develop vision and roadmap for compute frameworks and validation pipelines
Collaborate with AI teams for dataset automation
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Advise partners on evaluating, integrating, and optimizing payroll solutions
Collaborate with sales to design holistic API-driven solutions
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Provide technical leadership
Ensure software reliability and availability
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Develop state-of-the-art voice cloning and text-to-speech solutions
Implement low latency and cost-effective systems
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Guide customers through product journey
Build demos and prototypes
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Enhance AI systems through code validation and refinement
Validate algorithms for technical accuracy
