Buzz Solutions

• Define and drive the technical vision and architecture for our product PowerAI • Lead design and scaling of distributed systems and backend services, AI/ML pipelines and computer vision systems • Establish best practices across all engineering teams and projects • Lead & mentor team leads and senior engineers • Build a high performing engineering culture • Provide coaching, feedback and career development • Partner with other departments to define roadmaps and priorities • Ensure high-quality, on-time solutions to our customers • Work closely with leadership in discussions revolving around strategy an company direction

• Bring a rolodex of contacts from investor-owned, municipal, and cooperative utilities across North America • Create sustainable long-term relationships by providing win-win business solutions to utility clients in US • Develop new leads for prospective utility clients and inform regional priorities • Own key relationships with utility leaders, including executives and team leaders focused on grid modernization, transmission and distribution infrastructure inspections, asset and vegetation management, grid planning, and operations teams • Attend and present at select trade shows and conferences • Write formal project proposals, develop presentation slides, and other tools • Understand utility needs and pain points. Drive deployment scoping with utilities to balance stakeholder needs, internally and externally, and close deals that achieve both scale and rapid execution • Negotiate contracts through final execution • Consistently ensure that business is conducted with integrity at all times • Exercise indirect influence to maintain efficient and timely forward project progress • Support project manager to smoothly transition new contracts into implementation • Coordinate with fellow associates and co-founders on sales process improvements, product development, regulatory and policy goals, and competitive landscape • Knowledge in sales of B2B, SaaS products to enterprise clients (Energy experience is strongly recommended, though not required) • Coach SDRs on nurturing leads and to foster stronger pipeline • Maintain Hubspot and keep management and other key stakeholders appraised on sales activities and pipeline • Exceed sales targets by building and executing on an aggressive pipeline of investor-owned, municipal, and cooperative utilities

• Identify and research potential clients within the electric utility space. Utilize various tools and methods to build a strong pipeline of qualified leads. • Conduct outreach via phone calls, emails, and in person events to introduce our AI solutions and create interest among prospective clients. • Engage with prospects to understand their needs, challenges, and budget. Assess whether our solutions are a good fit and ensure leads meet our criteria for the sales team. • Schedule meetings and product demonstrations for the sales team with qualified leads. • Stay informed about industry trends, competitors, and market dynamics to effectively position our solutions and provide valuable insights to the team. • Work closely with the sales and marketing teams to align strategies, share feedback, and contribute to campaign development. • Maintain accurate and up-to-date records of interactions with prospects in our CRM system. Track performance metrics and report on progress regularly.

• Stay current with ML/CV research, identify promising methods, and evaluate their applicability to our domain • Adapt and implement algorithms from papers, validating against baselines and benchmarking for production viability • Own and deliver end-to-end computer vision projects focused on: • Design and execute experiments with systematic hyperparameter tuning, ablation studies, and appropriate baselines • Perform structured error analysis: categorize failure modes (false positives, missed detections, localization errors, misclassifications) and break down performance by data slices (object size, occlusion, image quality) • Select and justify model architectures based on task requirements, latency, and accuracy tradeoffs • Design and implement data pipelines including ingestion, preprocessing, annotation workflows, and quality monitoring • Experiment tracking and model versioning (configurations, random seeds, dataset versions, environment specs, and model checkpoints) • Build model serving pipelines that meet latency and throughput requirements • Conduct thorough code reviews and write integration tests for ML pipelines • Communicate research findings, technical decisions, and model limitations clearly to stakeholders

• Bring a rolodex of contacts from investor-owned, municipal, and cooperative utilities across North America • Create sustainable long-term relationships by providing win-win business solutions to utility clients in US • Develop new leads for prospective utility clients and inform regional priorities • Own key relationships with utility leaders, including executives and team leaders focused on grid modernization, transmission and distribution infrastructure inspections, asset and vegetation management, grid planning, and operations teams • Attend and present at select trade shows and conferences • Write formal project proposals, develop presentation slides, and other tools • Understand utility needs and pain points. Drive deployment scoping with utilities to balance stakeholder needs, internally and externally, and close deals that achieve both scale and rapid execution • Negotiate contracts through final execution • Consistently ensure that business is conducted with integrity at all times • Exercise indirect influence to maintain efficient and timely forward project progress • Support project manager to smoothly transition new contracts into implementation • Coordinate with fellow associates and co-founders on sales process improvements, product development, regulatory and policy goals, and competitive landscape • Knowledge in sales of B2B, SaaS products to enterprise clients (Energy experience is strongly recommended, though not required) • Coach SDRs on nurturing leads and to foster stronger pipeline • Maintain Hubspot and keep management and other key stakeholders appraised on sales activities and pipeline • Exceed sales targets by building and executing on an aggressive pipeline of investor-owned, municipal, and cooperative utilities

• Design, build, and maintain scalable training infrastructure for computer vision workloads • Implement and manage distributed training pipelines (multi-GPU, multi-node) to support large-scale model training and hyperparameter tuning • Build and maintain robust data pipelines for ML development • Design database schemas and storage strategies for managing large training datasets, annotations, and model artifacts • Implement and manage feature stores, data versioning, and experiment tracking to support reliable model iteration • Automate existing analysis workflows • Maintain clear documentation for platform components, data contracts, and deployment processes • Communicate infrastructure decisions, tradeoffs, and system limitations clearly to ML engineers and stakeholders • Conduct thorough code reviews and write integration tests for ML pipelines

• Architect and lead end-to-end computer vision projects focused on: Equipment defect detection, Thermal anomaly identification, Vegetation encroachment monitoring, Surveillance of closed areas for human and animal intrusions • Drive innovation by incorporating the latest advances in deep learning and generative AI to enhance model training, accuracy and reliability • Develop production-grade Python libraries for the complete ML lifecycle • Mentor team members and establish best practices for model development, evaluation, deployment, and monitoring • Advocate for and uphold software quality standards within the ML team

Join Buzz Solutions and be part of a dynamic team that is shaping the future of energy and technology. If you are passionate about delivering exceptional customer support and thrive in a collaborative and innovative environment, we want to hear from you! Apply now to embark on an exciting journey with us. Responsibilities - Develop end-to-end backend pipelines for deploying machine learning models. - Build Docker containers for trained machine learning models. - Deploy Docker container images on Kubernetes engine. - Maintain Kubernetes engine and virtual machines on Google Cloud Platform. - Develop Flask and FastAPI frameworks in Python for deploying models as APIs. - Deploy the models in production as REST APIs on cloud infrastructure. - Observe and measure current product performance. - Review the process and product performance data with the team to develop standard work. - Document the process, code reviews and workflow to streamline product enhancements. - Develop end-to-end pipeline for deploying software platform backend infrastructure. - Build end-to-end methodology for backend modules of the cloud software platform. - Choose the optimal technology stack for building out the elements of the software platform backend. - Establish platform features and timelines for product roadmap. - Integrate SQL database objects with the software platform. - Integrate machine learning model REST API endpoints with software platform. - Deploy the platform in production on cloud infrastructure. - Work with a team of software engineers to enhance performance of the software platform and run continuous unit tests for deployed products. - Observe and measure current product performance. - Review the process and product performance data w/ team to develop standard work. - Document the process, code reviews and workflow to streamline product enhancements. - Maintain and monitor cloud infrastructure. - Monitor the logs of customer usage of the products and test for any vulnerabilities. - Maintain database systems and optimize for performance and costs. - Provide unit and stress testing frameworks for cloud infrastructure services deployed in production environments. - Document the process, code reviews and workflow to streamline product enhancements. Qualifications - Must have a Bachelor’s degree in Computer Science or related field and 4 years of experience, including: - Designing, implementing, debugging web technologies and server architectures (Java,JavaScript, NodeJS), databases in Cloud Infrastructure and with Python programming language - Develop applications, API integrations on cloud infrastructures to handle customer data - Utilizing and maintaining cloud infrastructure and services of Google Cloud Platform - Employer will accept a Master’s degree and 2 years’ experience in lieu of the Bachelor’s plus 4.

• Develop end-to-end backend pipelines for deploying machine learning models. • Build Docker containers for trained machine learning models. • Deploy Docker container images on Kubernetes engine. • Maintain Kubernetes engine and virtual machines on Google Cloud Platform. • Develop Flask and FastAPI frameworks in Python for deploying models as APIs. • Deploy the models in production as REST APIs on cloud infrastructure. • Observe and measure current product performance. • Review the process and product performance data with the team to develop standard work. • Document the process, code reviews and workflow to streamline product enhancements. • Develop end-to-end pipeline for deploying software platform backend infrastructure. • Build end-to-end methodology for backend modules of the cloud software platform. • Choose the optimal technology stack for building out the elements of the software platform backend. • Establish platform features and timelines for product roadmap. • Integrate SQL database objects with the software platform. • Integrate machine learning model REST API endpoints with software platform. • Deploy the platform in production on cloud infrastructure. • Work with a team of software engineers to enhance performance of the software platform and run continuous unit tests for deployed products. • Observe and measure current product performance. • Review the process and product performance data w/ team to develop standard work. • Document the process, code reviews and workflow to streamline product enhancements. • Maintain and monitor cloud infrastructure. • Monitor the logs of customer usage of the products and test for any vulnerabilities. • Maintain database systems and optimize for performance and costs. • Provide unit and stress testing frameworks for cloud infrastructure services deployed in production environments. • Document the process, code reviews and workflow to streamline product enhancements.

• Design, develop, and execute test plans, test cases, and test scripts for web applications • Perform manual and automated testing across functional, regression, integration, and end-to-end scenarios • Collaborate with product managers and engineers to understand requirements and acceptance criteria • Identify, document, and track bugs with clear reproduction steps and severity levels • Validate fixes and ensure issues are resolved without introducing regressions • Build and maintain automated test frameworks and CI/CD test pipelines (where applicable) • Participate in sprint planning, backlog grooming, and release readiness reviews • Advocate for quality best practices across the development lifecycle • Continuously improve QA processes, tooling, and coverage