3 jobs found

Job Description Job Description Job Title: Senior Desktop Infrastructure Engineer Duration: 6 Months contract Location: Chicago, IL - The ideal candidate will be onsite 2 days per month for this role. Job Description: Core Ownership Areas Azure Virtual Desktop Nerdio Windows 11 Gold Images FSLogix Intune and Autopilot Integration End User Compute Architecture Azure Networking for AVD Desktop Infrastructure Automation Endpoint Security and Compliance Primary Responsibilities Azure Virtual Desktop Architecture & Operations Architect, implement, and maintain Azure Virtual Desktop environments. Design and manage host pools, session hosts, image lifecycles, and deployment pipelines. Develop scalability, resiliency, and disaster recovery strategies. Optimize user experience, performance, and Azure consumption costs. Establish operational standards and platform governance. AVD Networking & Infrastructure Engineering Design and troubleshoot AVD network connectivity across Azure and on-premises environments. Serve as the primary escalation point for network-related virtual desktop issues. Diagnose and resolve DNS, routing, firewall, latency, authentication, and connectivity problems. Partner with Network Engineering on ExpressRoute, VPN, segmentation, and hybrid connectivity solutions. Optimize network paths and client connectivity performance for virtual desktop workloads. Troubleshoot FSLogix profile performance, storage connectivity, and authentication issues. Analyze packet captures, connection diagnostics, and performance metrics to identify root causes. Support private endpoint, storage account, Azure Files, and Entra ID integration requirements. Nerdio Engineering & Automation Administer and optimize Nerdio Manager. Develop automated provisioning and image management workflows. Configure autoscaling and cost optimization strategies. Build operational automation using PowerShell and Azure services. Windows 11 Platform Engineering, Lead design and engineering of the Bank's Windows 11 desktop platform. Own gold image architecture and standards. Establish image testing, validation, and release processes. Define desktop lifecycle management strategy. Technical Leadership Provide technical leadership for desktop engineering initiatives. Mentor engineers and contractors. Establish engineering standards and operational practices. Evaluate vendors and technical solutions. Lead major incident response and root cause investigations. Required Skills Expert-Level Experience Azure Virtual Desktop Azure Networking Nerdio Microsoft Entra ID Active Directory Windows Desktop Engineering Windows 11 Image Engineering PowerShell Automation Root Cause Analysis and Troubleshooting Strong Experience FSLogix Azure Files DNS TCP/IP Networking Firewalls and Network Security Intune Autopilot Group Policy Preferred Experience EXPRESSROUTE Azure Virtual WAN Infrastructure as Code Ansible Liquidware ProfileUnity VMware Horizon or Citrix Terraform

Senior / Lead .NET Software Engineer / SRE DETAILS Location: Arlington, TX 76014 (hybrid onsite 2-days per week) Openings: 2 (1 Senior .NET / 1 Lead .NET) Position Type: 6M C2H Hourly / Salary: to $160K+ (based on experience level) JOB SUMMARY Vaco is currently seeking a Senior .NET Software Engineer / SRE for a 6M C2H opportunity that is located in Arlington, TX 76014 (hybrid onsite 2-days per week). About the Project: This is an ongoing multi-year digital transformation initiative (now roughly 2+ years in) focused on modernizing financial services platforms, making them more scalable, reliable, automated, and cloud-native. The .NET Engineer / SRE will be building and extending tools / frameworks for SRE practices, including automation scripts, custom monitoring, CI/CD enhancements, reliability tooling, etc. The .NET Engineer / SRE will help bridge the gap between development teams (writing .NET) and SREs (ensuring reliability at scale), especially within this strategic / tool building-focused SRE practice. This is not a traditional .NET Developer (no owning user-facing APIs or business logic for financial services), but rather applying .NET skills to SRE tasks, including building custom tools for automation, reliability, and release engineering, creating GITHub Copilot context files to embed SRE practices (security / performance checks) early in development cycles, debugging / refactoring code in production environments, performing root-cause analysis, and iterating post-deployment. Additionally, there's no traditional on-call production monitoring / support, whereas the focus will be on design, architecture, automation, and enabling scalable DevOps / SRE practices for development teams, rather than day-to-day firefighting. Ideal Senior Candidate:The ideal candidate will come with a Developer-First Mindset for full SDLC, Architecture Ownership, and Problem Solving (build the tool if it does not exist approach). Having .NET fluency enables strategic SRE in their .NET / Azure ecosystem, bridging gaps between development and operations without siloed roles. The Senior Engineer MUST be able to walk through their most recent projects, in depth, describing complex features, debugging, and development frameworks (why you'd choose one over the other for particular tasks, etc.). Ideal LEAD Candidate (leading teams of 5+): The ideal candidate will come with a Developer-First Mindset for full SDLC, Architecture Ownership, and Problem Solving (build the tool if it does not exist approach). Having .NET fluency enables strategic SRE in their .NET / Azure ecosystem, bridging gaps between development and operations without siloed roles. The Lead Engineer MUST be able to walk through their most recent projects, in depth, describing complex features, debugging, and development frameworks (why you'd choose one over the other for particular tasks, etc.). JOB REQUIREMETS .NET Core Development (hands-on core expertise) - C# / .NET Core Development Building / Maintaining Production-Grade Applications / APIs / Services Cloud Modernization - Migrating Legacy .NET Applications to Cloud-Native Azure Architectures Azure-Native Application Development - Designing / Deploying / Supporting .NET Applications Directly in Azure with Real Production Workloads (Beyond Portal-Based "Click-Ops") AKS / Containerization - Containerizing .NET Applications (Docker Multi-Stage Builds) Deploying / Managing within AKS (Deployments / Services / ConfigMaps / Secrets / Helm / Node Pools / Autoscaling / Ingress / Cluster-Level Troubleshooting) CI/CD / Azure DevOps - Building / Maintaining YAML-Based CI/CD Pipelines (Automated Builds / Testing / Security Scans / Docker Image Creation / Deployments to AKS / App Services) Azure Platform Services Integration - Integrating Core Azure Services into .NET Applications (App Services / Azure Functions / Service Bus / Event Grid / Azure Monitor / Application Insights With Custom Telemetry / Distributed Tracing / Metrics) IaC / Terraform - Developing / Managing Terraform-Based Infrastructure (AKS / VNETs / Private Endpoints / Service Bus / SQL Database / Storage) Aligned with Application Development Identity / Security (Azure) - Implementing Secure Patterns (Managed Identities / Entra ID / RBAC / Secure Connectivity / Polly Retry Policies / Private Endpoints / VNET Integration) within .NET Services Observability / SRE Practices - Applying SRE Principles within Development (Application Insights / Log Analytics / Alerting / Performance Monitoring / Production Troubleshooting) Database Design / Optimization - Oracle / MS SQL Server / NoSQL (CosmosDB) SQL Scripting (hands-on) Designing / Evolving Database Schemas Performing Query Performance Analysis Indexing to Deliver Scalable / Performant Services Problem Solving / Collaboration - Driving Root Cause Analysis / Debugging for .NET Applications in Azure Collaborating within SRE / Cross-Functional Teams PREFERRED (not required) Azure Governance / Best Practices - Azure Policy / GitHub Copilot Context / Embedding SRE Practices Early in Development Lifecycle Architecture Frameworks (Familiarity) - Azure Well-Architected Framework (Reliability / Operational Excellence) Advanced AKS / Hybrid - Exposure to Advanced AKS Topics (Cluster Autoscaling / Service Mesh / Cost Optimization) / Hybrid Scenarios (Azure Arc) AI / Automation Enablement - Driving Adoption of AI-Powered Tools (GitHub Copilot) to Improve Developer Productivity / Code Quality By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. EEO Notice Vaco by Highspring is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race (including but not limited to traits historically associated with race such as hair texture and hair style), color, sex (includes pregnancy or related conditions), religion or creed, national origin, citizenship, age, disability, status as a veteran, union membership, ethnicity, gender, gender identity, gender expression, sexual orientation, marital status, political affiliation, or any other protected characteristics as required by federal, state or local law. Vaco by Highspring and its parents, affiliates, and subsidiaries are committed to the full inclusion of all qualified individuals. As part of this commitment, Vaco by Highspring and its parents, affiliates, and subsidiaries will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact . Vaco by Highspring also wants all applicants to know their rights that workplace discrimination is illegal. Representation Notice By submitting to this position, you agree that you will be giving Vaco by Highspring the exclusive right to present your as a candidate for the foregoing employment opportunity. You further agree that you have represented information about yourself accurately and have not affirmatively misrepresented your qualifications. You also agree to maintain as confidential, to the fullest extent permitted by law, any information you learn from Vaco by Highspring about the position and you will limit disclosure of information about the position only to the extent necessary to perform any obligations in furtherance of your application. In exchange, Vaco by Highspring agrees to exercise reasonable efforts to represent you through all solicitation, job screening and resume dispersal. For residents of Ontario, Canada: Based on Highspring's discussions with its Client, Highspring's understanding is that this position for employment is a current vacancy (either through Highspring as a contractor or with the client directly). Privacy Notice Vaco by Highspring and its parents, affiliates, and subsidiaries ("we," "our," or "Vaco by Highspring") respects your privacy and are committed to providing transparent notice of our policies. California residents may access Vaco by Highspring HR Notice at Collection for California Applicants and Employees here. Virginia residents may access our state specific policies here. Residents of all other states may access our policies here. Canadian residents may access our policies in English here and in French here. Residents of countries governed by GDPR may access our policies here. Additionally, submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. More details about Vaco by Highspring's use of AI can be found here (). Further assessment of candidates beyond this initial phase will be conducted by recruiters and hiring managers. Vaco by Highspring does not know and cannot opine on if its client's use of AI products in hiring. Pay Transparency Notice Determining compensation for this role (and others) at Vaco by Highspring depends upon a wide array of factors including but not limited to: the individual's skill sets, experience and training; licensure and certification requirements; office location and other geographic considerations; other business and organizational needs. With that said, as required by local law, Vaco by Highspring believes that the following salary range referenced above reasonably estimates the base compensation for an individual hired into this position in geographies that require salary range disclosure. The individual may also be eligible for discretionary bonuses.

Job Description Job Description About ATI: Automated Tire (ATI) is a Series-B startup revolutionizing automotive service with innovative robotic and software technology. Founded by experienced entrepreneurs and backed by major players in the automotive and tire sectors, ATI is building the next generation of tools that make tire shops and dealership service lanes faster, safer, and smarter. If you're passionate about building products that ship into real-world environments, ATI is the place for you. Position Overview: BrakeWise is our production brake inspection product: a mobile application paired with a camera probe that technicians use to assess pad and rotor condition during live service work. The machine learning behind it is a multi-stage pipeline of segmentation and classification models that turn raw imagery into a wear assessment a shop can act on and charge for. That pipeline works, and it is an MVP. It runs on Cloud Functions, and it will not carry us to the customer volume we're signing. We're looking for a Staff MLOps Engineer to own it - to take it from a working prototype to a serving architecture that holds up under real throughput, with the latency, cost, and reliability characteristics a paying customer expects. You'll own every aspect of how our models reach production and how they get better: serving infrastructure, deployment and rollback, monitoring and drift detection, the retraining loop, and the evaluation discipline that tells us whether a new model is actually an improvement. Model accuracy here has commercial consequences - a bad wear call is either a missed repair or an unnecessary one, in front of a customer. This is also the senior cloud architecture voice on the team. You'll partner closely with our Staff Full Stack Engineer, who owns the mobile app and customer dashboard, reviewing designs and setting GCP practices across the platform rather than only within the ML stack. Responsibilities: Own the multi-stage inference pipeline (segmentors and classifiers) end to end - serving architecture, latency, throughput, reliability, and cost per inspection Re-architect the pipeline off its current Cloud Functions MVP onto infrastructure that scales: containerized inference, GPU-backed or accelerated serving where it pays for itself, queueing, batching, and autoscaling Own model deployment: versioning, staged rollout, canary and shadow evaluation, and fast rollback when a model regresses Build and own the improvement loop - field data collection, labeling workflows, dataset versioning, evaluation harnesses, and regression suites that catch quality loss before customers do Monitor model quality in production: drift detection, segmented performance analysis, and triage of real-world failures against real inspection imagery Define the metrics that matter commercially - false-positive and false-negative rates on a wear call, technician override rate, unit inference cost - and report against them Improve model performance directly: architecture selection, augmentation, hard-example mining, and quantization or distillation where latency and cost demand it Evaluate on-device versus cloud inference trade-offs for the mobile app, and own whichever path we choose Establish MLOps foundations: reproducible training, experiment tracking, CI/CD for models, and infrastructure as code Serve as the cloud architecture counterpart to the Staff Full Stack Engineer - reviewing designs, setting GCP best practices, and raising the platform's infrastructure bar Work with hardware and field operations on capture quality - lighting, focus, and probe positioning - since upstream image quality sets the ceiling on model performance Own production support for the ML stack, including incident response and on-call participation for inference availability Proactively identify technical risks and architectural trade-offs, and communicate them clearly to leadership Requirements 8+ years of professional engineering experience, including several years owning machine learning systems in production - not solely model development Demonstrated experience taking a computer vision pipeline from prototype to production scale, serving real users at meaningful volume Deep experience deploying and operating segmentation and classification models, including multi-stage pipelines where one model's output feeds the next Strong cloud infrastructure background, preferably GCP - Vertex AI, Cloud Run, GKE, Cloud Functions, Cloud SQL, Pub/Sub, and Docker Production-grade Python, and fluency with PyTorch or TensorFlow Hands-on experience with model serving and optimization - Triton, TorchServe, ONNX, TensorRT, quantization, or equivalent Experience owning deployment and support for a live system, including incident response, rollback, and on-call Experience building data and labeling pipelines with dataset versioning and reproducible evaluation Comfort with infrastructure as code (e.g., Terraform) and CI/CD automation (e.g., GitHub Actions) Sound judgment on the accuracy, latency, and cost trade-offs that determine whether an ML product is viable Excellent problem-solving, debugging, and communication skills, including with non-technical stakeholders Preferred Qualifications: On-device or edge inference experience (Core ML, TensorFlow Lite, ExecuTorch) and integration into mobile applications Active learning or human-in-the-loop labeling systems Computer vision on small, long-tail, or industrial inspection datasets rather than large public benchmarks Experience with camera and sensor integration, or working alongside hardware teams on capture quality Experience with robotics, IoT, or edge computing (ROS or similar platforms) Familiarity with automotive service, dealership operations, or DMS ecosystems Contributions to open-source projects Why Join ATI: Be part of a groundbreaking startup transforming automotive service technology Work with a team of industry veterans and top-tier robotics and software talent Own the ML platform for a product that already has paying customers - your architecture decisions set the scaling ceiling Our customers are our investors, so you'll develop and test in real service lane environments A genuine data advantage: proprietary inspection imagery from real shops that no public dataset can replicate Clear Total Addressable Market with strong pull from B2B partners Competitive salary and comprehensive benefits package Prime location in Woburn, MA with on-site parking Collaborative, low-ego, high-intensity work environment