Job Description: A Machine Learning Engineer helps our learners discover content that is relevant to their interests and goals, providing them with experiences tailored just to their needs, and ensure they are receiving the right communication and assistance with their journey at the right time. They develop robust, scalable production machine learning algorithms and recommendation systems. Who you’re committed to being: - You enjoy learning and are open to new ways of doing things. - You are not afraid to be yourself, experiment, make mistakes and learn from them, ask questions, or voice your concerns. - When communicating you are self-aware, insightful, and proactive. What you’ll do: - Work closely with Data Scientists to take prototype algorithms and models and turn them into customer-facing solutions - Build solutions to novel problems in software development, data engineering, and machine learning - Build data pipelines; transform and convert data streams into structures needed for algorithm input - Collaborate with Product Managers and UX Designers to better understand the customer, provide valuable input into functional design and usability - Evaluate the efficiency of user experiences and ML algorithms, determining what data is needed and how to collect it, with an understanding of how these metrics are connected with the desired outcomes Experience you’ll bring: - Experience building production machine learning systems services as part of a product development team - Experience in Python, TensorFlow, and proficiency in data structures and database fundamentals - Experience building good code with speed and efficiency and balancing the trade-offs of quality vs speed - Ability to explain machine learning solutions to developers and other team members, regardless of their technical background - Experience working with continuous integration and delivery - Familiarity with cloud platforms and deploying ML models as scalable services - Experience with containerization and orchestration tools such as Docker and Kubernetes - Knowledge of software design patterns and best practices, including RESTful API design - Ideal experience in using machine learning in the context of recommendations and/or personalization. - Experience with Node and Typescript preferred Requirements: - Requires a minimum of 5 years of related or equivalent experience; or 3+ years with an advanced degree - This is a remote role; however, applicants located within 45 miles of our Westlake/Dallas, TX office should expect to work on-site Tuesday through Thursday, with remote flexibility on Mondays and Fridays. This approach enables more effective collaboration, quicker decision-making, and a stronger culture, while still providing flexibility. Why you’ll love working here: - We work in a blended environment that supports collaboration, flexibility, and connection across teams. - We are mission-driven, shaping the future of tech upskillling and delivering impact that matters. - We foster a culture of inclusion and belonging, where everyone can contribute and thrive. - We are always learning, creating an environment where you can take on new challenges, expand your skills, and grow with purpose. - Benefits include competitive compensation, bonus eligibility, comprehensive medical coverage, unlimited PTO, wellness reimbursement, professional development funds, and more. About us: Pluralsight provides the only learning platform dedicated to accelerating the technology skills and capabilities of today’s tech workforce. Thousands of companies, government organizations and individuals around the world rely on Pluralsight to support critical technology skill development in areas that are crucial to innovation including artificial intelligence, cloud computing, cybersecurity, software development, and machine learning. We offer highly curated content developed by vetted technology experts, industry leading skill assessments, and hands on, immersive learning experiences designed to help individuals skill-up faster. Physical Requirements: This role is primarily performed in an office or home office setting and involves standard computer-based work. EEOC & Accommodations Statement: Bring yourself. Pluralsight is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or veteran status. We also consider qualified applicants with criminal histories, consistent with EEOC guidelines and local laws. If you need an accommodation to apply, interview, or perform essential job functions, please visit the bottom of our website to learn how to request an accommodation. Learn more about our commitment to diversity, equity, inclusion, and belonging in our DEIB Report. Pay Transparency: The annual US base salary range for this role is $121,600 - $160,000 USD. Actual compensation will depend on location, skills, experience, and other factors. Additional benefits and bonuses may apply. Pay Transparency: The annual US base + variable range for this role is $[OTE min] - $[OTE mid] USD. Actual compensation will depend on location, skills, experience, and other factors. Additional benefits and bonuses may apply. Applications must be submitted within 90 days after the initial posting date to be considered. Recruiting Scam Notice: Please be aware of recruiting scams. We’ll only contact you from an @pluralsight.com email or verified channels. We never ask for sensitive personal info or payments as part of the hiring process. All openings are posted on our Careers page. #LI-DB1

• 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.