• Build and improve inventory demand forecasting models using ML and statistical methods. • Own ML models end-to-end: data collection → feature engineering → training → deployment → monitoring → iteration. • Develop decision systems that support inventory planning, pricing, and demand decisions. • Build and maintain data pipelines and API integrations for external and internal data sources. • Work with messy real-world data to ensure model reliability through rigorous validation and testing. • Implement LLM/AI-agent workflows to translate domain logic into automated processes. • Operate independently in a small team, setting priorities, unblocking challenges, and communicating tradeoffs clearly.

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.

Role Description We're looking for a Senior Machine Learning Engineer to help us unlock the next wave of value from our data. This is our first dedicated ML role - you'll be the person who establishes how machine learning is done here. - You'll sit within the Data Engineering Squad and take ownership of ML use cases end-to-end - from identifying opportunities with stakeholders through to deploying and monitoring models in production. - This is a hands-on senior individual contributor role. - You won't manage people directly, but you will help shape our ML strategy alongside the Head of Data Engineering, Director of Analytics and Insight, and our incoming Chief Product Officer. - While you'll be the primary ML specialist, you'll have strong support from Data Engineers, Analytics Engineers, and a leadership team that is actively investing in advanced analytics and AI. - The company has an OKR to deliver multiple AI experiments each quarter - some will be selected and sponsored by the leadership team, but you'll also have significant freedom to drive your own agenda and identify opportunities independently. - Our platform runs on Azure and Databricks. You'll work within that ecosystem to design, build and scale ML solutions that are reliable, observable and cost-effective. - The current workload is primarily batch-oriented, with the business moving towards event-driven patterns across operational and analytics platforms - an early-stage journey you'll have the opportunity to help shape. Qualifications - Substantial experience in machine learning engineering, with a track record of deploying and maintaining models in a commercial product context - not just internal tooling. - Demonstrated ability to work across the full ML lifecycle at a level where you're making design trade-offs, influencing system architecture and driving quality standards - not just building to a spec. - Deep understanding of ML fundamentals - feature engineering, model selection, evaluation, hyperparameter tuning and the practical trade-offs involved. - Experience designing and operating ML pipelines and infrastructure using IaC principles. - Practical experience with MLflow or equivalent experiment tracking and model registry tooling. - Strong proficiency in Python and SQL, and hands-on experience with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow. - Excellent communication skills - you can translate technical concepts for non-technical stakeholders and build consensus across teams. Requirements - Experience with Databricks (ML Runtime, Feature Store, Unity Catalog, Model Serving). - Familiarity with Azure ML services and AKS or container-based model serving architectures. - Hands-on experience with Terraform, with a self-serve mindset towards provisioning and managing infrastructure. - Exposure to LLMs, generative AI or agentic patterns - we see this as a growth area and would value someone who can help us navigate it. - Awareness of data privacy, security and ML ethics considerations in a consumer-facing, data-rich environment. - Experience in marketplace, e-commerce or classified advertising domains. Benefits - A genuine greenfield ML opportunity - you'll be the first dedicated ML hire and will shape the roadmap from day one. - A modern data platform built on Databricks with strong Data Engineering foundations already in place. - A business with rich, diverse data across dealers, vehicles, listings, consumer behaviour and leads. - A leadership team actively investing in AI and advanced analytics, with a quarterly OKR cadence for experimentation. - If you're motivated by turning data into products that create business value, and you want the autonomy to define how ML works here, we'd love to hear from you.

Who we are Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale. Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term. About the role: Samsara is the industry leader in AI for physical operations. We’re hiring a Staff / Senior Staff Machine Learning Infrastructure Engineer to lead the design and evolution of our end-to-end ML platform powering Safety AI and adjacent product areas. This role combines deep platform ownership with direct product impact—enabling teams to build, deploy, and scale ML systems that improve real-world safety outcomes. This is a remote position open to candidates based in the United States. You should apply if: - You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely. - You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations. - You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go. - You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes. - You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together. In this role, you will: - Design, build, and operate Samsara’s end-to-end ML platform spanning training, experimentation, batch and online inference, and edge deployment, used by multiple product teams across Safety AI and adjacent domains. - Partner with product and applied ML teams to design, launch, and iterate ML-powered features (e.g., backend CV models, EcoDriving insights, LLM-based reporting), driving measurable improvements in safety outcomes, feature reliability, and cost efficiency. - Lead throughput and cost estimation for new ML features—from early-stage exploration to production-scale capacity planning—informing roadmap and go/no-go decisions. - Collaborate on experiment design and evaluation, including defining success metrics, structuring A/B tests or offline evaluations, and interpreting results to guide product and technical decisions. - Evolve shared training and experimentation infrastructure (e.g., job orchestration, cluster configuration, environment management), and standardize experiment tracking, evaluation, and regression testing to enable fast and safe iteration. - Design and operate scalable online and batch inference systems (Ray- and Spark-based), including deployment patterns, observability, and SLOs, while unifying training-to-production workflows and enabling consistent pipelines across teams. - Partner with firmware and edge teams to define workflows for packaging, validating, and deploying models to Samsara devices, and build feedback loops from edge to cloud to support continuous improvement. - Own the reliability, observability, and security posture of ML systems across cloud and edge environments, including on-call practices, incident response, and infrastructure hardening. - Provide Staff+/Senior-Staff-level technical leadership by setting architecture and strategy for ML infrastructure, influencing cross-team decisions, and mentoring engineers and applied scientists. - Drive strong developer experience through documentation, office hours, and best practices, while contributing to and representing Samsara in open source communities (e.g., Ray, Spark, RayDP). - Own or co-own end-to-end technical delivery for high-priority or high-risk initiatives, from modeling and system design through production rollout. - Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices. Minimum requirements for the role: - 10+ years of overall experience in machine learning engineering or related fields, with a strong track record of building and operating large-scale ML systems. - Strong experience with distributed computing frameworks such as Ray and/or Spark. - Hands-on experience with cloud infrastructure (AWS), containers/Kubernetes, and production observability tooling. - Proven experience building or supporting ML platforms (training, experimentation, or inference) used by multiple teams. - Solid understanding of ML fundamentals including evaluation, experiment design, and model iteration in production environments. An ideal candidate also has: - Experience shipping ML-powered features end-to-end, from design through production and iteration, with measurable impact on product or business metrics. - Background in computer vision and/or LLM-based systems in production environments. - Experience with edge or on-device ML and collaboration with firmware or embedded teams. - Familiarity with model lifecycle systems (model registry, deployment, monitoring, rollback, drift detection). - Experience working in environments with strong security and compliance requirements. - Demonstrated ability to lead across teams and influence technical direction at Staff+ scope. - A strong sense of ownership and a desire for end-to-end autonomy—from platform design to real-world impact. The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below. Annual Base Salary $200,200—$357,500 USD Total Rewards At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time. Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here. Flexible Working At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable. Belonging at Samsara At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact. Accommodations Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process. Our Commitment to Authenticity We use Tofu, a fraud detection tool, to validate the authenticity of applications and protect against identity fraud. This ensures we are connecting with real people and allows us to prioritize genuine candidates. Please see Samsara’s Candidate Privacy Notice for more information. Fraudulent Employment Offers Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in @samsara.com, @us-greenhouse-mail.io or @mail3.guide.co. For more information regarding fraudulent employment offers, please visit our blog post here.