About Us

Buzz is revolutionizing the analytics and maintenance of power grid infrastructure through our advanced AI solutions. Our computer vision systems analyze critical infrastructure to enhance safety, reliability, and operational efficiency across the power grid network.

Job Description 

We're looking for an entry/mid-level Applied Machine Learning Platform Engineer to join our computer vision team and help improve the databases, cloud infrastructure, and tooling our team builds on. You'll build tooling and infrastructure to help scale our training and data pipelines. You'll work within a team of experienced ML engineers with the autonomy to drive your own projects and the support to keep growing.

Responsibilities

• 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

Qualifications & Experience

• 2-4 years of industry experience in platform, backend, data, or MLOps engineering roles
• Python proficiency — idiomatic code, type hints, async patterns, packaging, and performance-aware implementation
• Strong software engineering fundamentals — testing, code review, API design, component-level system design
• Hands-on experience building and operating distributed cloud machine learning infrastructure
• Designing and maintaining scalable training infrastructure, managing ML platform reliability, optimizing data pipelines for throughput at scale
• Experience with database design and data systems for ML workloads — schema design, query optimization, and storage strategies for large-scale datasets
• Excels at workflow orchestration and automation
• Solid proficiency in Python and core ML tooling:
  • Python ecosystem: Pytest, UV, FastAPI, Pydantic
  • Tooling: Git, Docker, UV
  • Tracking: MLflow, Weights & Biases, or equivalent
  • Automation: Github Actions, CI/CD, Prefect or equivalent
  • Infrastructure: AWS, GCP, Kubernetes, Helm, Terraform or equivalent
  • Databases: postgres, DynamoDB, Bigtable

* Buzz Solutions does not provide Visa sponsorship for work authorizations in the United States at this time *

About Us

Buzz Solutions is a fast-growing startup focused on applying AI and computer vision to solve real-world challenges in the energy and utility space. Our platform helps utilities improve reliability, safety, and operational efficiency through advanced machine learning and scalable software systems.

Job Description 

We are seeking an experienced Director of Engineering to lead and scale our engineering organization across AI, infrastructure, and platform systems. This is a high-impact leadership role that blends deep technical ownership including architecture, AI systems, and cloud infrastructure with strong people leadership across a multi-team organization. This individual will also close strategically and collaboratively with Product, Solutions, and executive leadership. In this role, you will directly manage team leads across three core pillars: Computer Vision and AI, MLOps and systems infrastructure, and platform engineering.

Responsibilities

• 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

Qualifications & Experience

• 12+ years in software engineering (SaaS, infrastructure, and AI systems)
• 6+ years leading engineering teams in a hands-ons capacity
• Background in AI-driven SaaS platforms
• Experience scaling engineering at high-growth startups
• Proven experience managing multi-team orgs
• AI / ML systems experience is a must, preferably within computer vision projects
• Strong understanding of distributed systems, backend architecture, MLOps pipelines, and Full Stack Systems 

Plus if you have:

• Experience energy or industrial systems
• Experience with drone, imagery, or geospatial systems

* Buzz Solutions does not provide Visa sponsorship for work authorizations in the United States at this time *

About Us

Buzz is revolutionizing the analytics and maintenance of power grid infrastructure through our advanced AI solutions. Our computer vision systems analyze critical infrastructure to enhance safety, reliability, and operational efficiency across the power grid network.

Job Description 

We're looking for a Machine Learning Engineer to join our computer vision team and help build our foundational model capabilities. You'll bridge the gap between cutting-edge research and production systems, reading papers, adapting novel algorithms, and turning them into reliable, deployed models for power grid analysis. You'll work within a team of experienced ML engineers, with the autonomy to drive your own projects and the support to keep growing.

Responsibilities

• 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:
  • Equipment defect detection
  • Thermal anomaly identification
  • Vegetation encroachment monitoring
• 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

Qualifications & Experience

• 2-4 years of industry experience in computer vision and machine learning
• Solid understanding of modern computer vision and deep neural networks including:
  • Object detection
  • Semantic segmentation
  • Image classification
  • Vision transformers and foundation models
• Demonstrated ability to read ML research papers, extract key ideas, and implement them
• Experience adapting published methods to specific use cases and validating against baselines
• Experience selecting, fine-tuning, and adapting model architectures (CNNs, transformers, foundation models) for specific use cases
• Ability to debug training instabilities and conduct systematic error analysis
• Proficiency in Python and core ML libraries:
  • PyTorch and Lightning
  • OpenCV
  • NumPy and pandas
  • Scikit-Learn
• Strong software engineering practices:
  • Git version control
  • Unit and integration testing (Pytest)
  • CI/CD pipelines (GitHub Actions)
  • Experiment tracking and model versioning
  • Docker and reproducible environments
  • Python type hinting

* Buzz Solutions does not provide Visa sponsorship for work authorizations in the United States at this time *

We are looking for a detail-oriented and driven QA Engineer to ensure the quality, reliability, and performance of our software products. You will work closely with engineering, product, and design teams to validate new features, prevent regressions, and continuously improve our testing practices. This role is critical to delivering a high-quality user experience at scale.

Responsibilities

• 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

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
• 5+ years of experience in software quality assurance or testing
• Strong understanding of software development lifecycles (Agile/Scrum)
• Able to adapt to testing depth based on ticket type (feature vs bug), impact, and release context rather than applying a one-size-fits-all approach.
• Experience with manual testing techniques and test case design
• Confident using browser DevTools (network, console, application/storage) to debug UI and API issues and collaborate effectively with engineers.
• Familiarity with bug tracking tools (e.g., Jira, Linear, GitHub Issues)
• Hands-on experience with JIRA workflows, BDD tools like Cucumber, CI pipelines, and comfort validating automated test results alongside manual testing.
• Ability to clearly communicate issues to technical and non-technical stakeholders
• Comfortable owning validation decisions, initiating QA–Dev syncs when needed, and partnering with engineers to improve product quality without adding unnecessary process.
• Strong attention to detail and a proactive mindset

Preferred Qualifications

• Experience with test automation frameworks (e.g., Playwright, Cypress, Selenium)
• Programming or scripting experience (JavaScript, Python, or similar)
• Experience testing APIs, backend services, or distributed systems
• Familiarity with CI/CD tools (GitHub Actions, GitLab CI, Jenkins)
• Experience testing cloud-based or data-intensive applications
• Knowledge of performance, load, or security testing is a plus

Job Description 

Buzz is revolutionizing the analytics and maintenance of power grid infrastructure through our advanced AI solutions. Our computer vision systems analyze critical infrastructure to enhance safety, reliability, and operational efficiency across the power grid network. We're seeking an experienced Machine Learning Engineer to help lead our computer vision initiatives. You'll drive the development of cutting-edge models for power grid analysis and provide a leadership anchor on a team of talented ML engineers.

Responsibilities

• 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

Qualifications & Experience

• 7-10 years of industry experience in computer vision and machine learning
• Deep expertise in modern computer vision and deep neural networks including: Object detection, Semantic segmentation, Image classification, Similarity search, Vision language models
• Proven track record of deploying and maintaining ML models in production
• Expert proficiency in PyTorch, Lightning, OpenCV, and Scikit-Learn
• Proficiency in FastAPI and Pydantic
• Strong software engineering foundation including: Git version control, Test driven development (Pytest), CI/CD, ML devops, Python type hinting
• 2-3 years of proven leadership experience of technical teams

Desired Additional Experience

• Multi-modal computer vision 
• Custom object detection model development
• Generative models for data augmentation
• ML deployment on edge devices
• Extracting measurements from GIS and/or drone metadata enriched imagery
• Model quantization
• Systematic hyperparameter tuning

Additional information:

• This position does not include sponsorship for United States work authorization.

• Design, develop, and maintain high-quality, scalable web applications and platform services.
• Build robust backend services and APIs using modern frameworks and cloud-native patterns.
• Develop user-friendly, performant frontend interfaces that deliver an exceptional user experience.
• Ensure code quality through best practices, automated testing, and continuous integration.
• Provide architectural direction, evaluate technical trade-offs, and guide long-term platform evolution.
• Establish engineering standards and promote best practices in software design, testing, and documentation.
• Collaborate with cross-functional teams—including product, QA, ML, and systems—to deliver high-impact features.
• Drive technical discussions, identify risks, and proactively remove blockers to ensure delivery timelines are met.
• Work closely with stakeholders to understand requirements and translate them into technical solutions.
• Participate in sprint planning, backlog refinement, and team-wide retrospectives to continuously improve workflow.
• Implement scalable, secure, and high-performance architectures across the stack.
• Monitor and optimize system performance, triage production issues, and drive root-cause analysis.
• Contribute to the evolution of deployment pipelines, observability tools, and platform operational excellence.

• 8-10+ years of fullstack engineering experience, with strong proficiency in modern backend (Node.js) and frontend (React, typescript) technologies.
• Demonstrated experience leading engineering projects or teams in a fast-paced, product-driven environment.
• Strong understanding of system design, API architecture, cloud environments (AWS/GCP/Azure), and CI/CD pipelines.
• Experience building scalable platforms handling large datasets or complex workflows (bonus for AI/ML systems).
• Excellent communication, collaboration, and problem-solving skills.
• Experience working with data-intensive applications, imagery/video pipelines, or AI-integrated systems.
• Familiarity with microservices architectures, containerization, and distributed systems.

** Buzz Solutions does not provide sponsorship for work authorizations in the United States at this time *

About The Role: 

As a Solutions Engineer, at Buzz Solutions, you will play a pivotal role in driving the adoption of our AI-powered solutions, PowerAI and PowerGUARD, within the electric utility sector. This role combines pre-sales technical consulting (60%) and post-sales customer enablement (40%), ensuring a seamless experience from initial engagement through solution adoption through AI / ML based projects.

This is a high-impact role for someone who thrives on solving complex problems, loves working directly with customers, and enjoys strategic thinking and hands-on execution. You will be the face of Buzz Solutions for some of the nation’s largest utilities, guiding them through adopting and integrating our AI solutions. You will engage in deep business and technical discovery, creatively position our value in their workflows, and collaborate closely to maximize their success. We are looking for someone who is self-driven, resourceful, and eager to grow—someone who sees this role as an opportunity to demonstrate their expertise, shape the future of AI in utilities, and make a real industry impact. If you enjoy working on a mix of technical challenges, client engagement, and strategic problem-solving, we want to hear from you. 

Key Responsibilities 

Sales Support:

• Gather customer requirements to understand and document our clients' needs and challenges.
• Architect and demonstrate AI/ML-powered solutions that meet client needs, including computer vision, data ingestion, analytics, and API integrations
• Collaborate closely with Account Executives to strengthen relationships and drive new business by leading the RFI/RFP process.
• Lead the design and deployment of end-to-end ML and computer vision workflows and solutions for utility clients and their use cases
• Collaborate with customer technical teams during deployment to ensure seamless integration, guide best practices, and optimize solutions for long-term success.
• Develop tailored solutions that meet customer requirements. 
• Complete Vendor Security Audits required by clients to ensure the security and compliance of our solutions with industry standards. 
• Answer technical questions from clients regarding our technology, features, and solutions. 
• Create compelling demos, visualizations, and technical presentations that clearly communicate the value of our AI-driven platform to both technical and non-technical audiences
• Provide comprehensive training sessions with clients, both virtually and onsite.
• Contribute to successfully implementing and integrating our solutions into clients’ workflows. 

Travel Requirements: 

• This role includes periodic travel to client locations and industry events. Candidates should be prepared for travel that may vary in frequency and duration based on project requirements.
• Travel will primarily be domestic (within the U.S.), with occasional international trips.
• Candidates should be flexible and available for occasional short-notice travel to meet client and project deadlines.
• All travel expenses, including transportation, accommodation, and meals, are covered by the company.
• A valid passport is required, and candidates should be able to obtain any necessary visas for international travel. 

Minimum Qualifications: 

• 5+ years of experience in a solutions engineering or sales engineering role, ideally 
  supporting AI/ML or data-driven software products
• Proven track record of building and operationalizing AI/ML workflows and solutions
•  Strong understanding of AI/ML concepts - neural network architectures, convolutional neural networks (detection, segmentation, classification based supervised learning
• High-level proficiency with computers and business software, including CRM systems, presentation tools, and productivity software (e.g., Microsoft Office Suite, HubSpot, Canva, etc.)
• Background working in and/or a solid understanding of cybersecurity and information security standards, including ISO 27001 and SOC2.
• Proven ability to build and strengthen customer relationships, guiding them through technical discovery and solution adoption.
• Excellent verbal and written communication skills to articulate complex technical concepts clearly to both technical and non-technical audiences.
• Strong problem-solving skills with the ability to understand customer needs and provide tailored solutions. 
• Experience with scripting or automation (e.g., Python, VBA) to improve personal efficiency and productivity.

Bonus Skills: 

• Experience selling, buying, or integrating Esri products like ArcGIS.
• Experience working in the Electric Utility Industry or Power Engineering Industry.
• Experience working as a field technician or field engineer in the utility industry, especially as a substation technician, utility inspector, or lineman.