Role Description We're looking for a Machine Learning Engineer to join our Insurance AI team. You'll be the engineering backbone for our Data Scientists, building and maintaining the ML infrastructure that turns models into reliable, scalable products. This isn't a greenfield build-everything-from-scratch role. Our Sydney-based AI & Computer Vision team has built robust ML tooling and pipelines. Your job is to extend, adapt, and maintain that infrastructure for US-specific use cases. If you're someone who gets satisfaction from making existing systems work better rather than reinventing the wheel, keep reading. You'll work closely with Data Scientists in the US and ML Engineers in Australia, acting as the technical bridge that keeps both teams moving fast. What You'll Do - Own the ML engineering function for the US Insurance AI team. - Build data and model pipelines, integrating with internal and external APIs. - Ensure Data Scientists have the tools they need to ship models to production. - Collaborate daily with our Sydney AICV team to leverage shared infrastructure and contribute improvements back. - Write Python, wrangle data pipelines, debug production issues, and translate Data Scientist requirements into working systems. - Use AWS, work with cloud-native technologies, and operate within an established MLOps framework. Key Responsibilities - Build and maintain ML pipelines for data ingestion, feature processing, model training, deployment, and monitoring in AWS. - Extend and adapt existing tooling from our Sydney AICV team for US Insurance AI use cases. - Develop and support internal tools and frameworks that streamline experimentation and improve delivery speed. - Integrate internal and external APIs to connect datasets, models, and services. - Partner with Data Scientists to understand their workflow needs and translate them into scalable technical solutions. - Ensure infrastructure supports rapid experimentation while maintaining reliability, security, and scalability. - Collaborate with Technical Product Managers, API engineers, and platform teams to deploy models in production. - Contribute to a shared codebase through feature branches, pull requests, and code reviews. Qualifications - 2-4 years as a Machine Learning Engineer or ML-focused Software Engineer. - Strong Python skills with a track record of writing clean, tested, production-grade code. - Hands-on experience with ML libraries like PyTorch, scikit-learn, and pandas. - Experience building and maintaining ML pipelines in production environments. - Solid SQL skills and familiarity with data engineering tools (Airflow, Spark, or dbt). - The ability to jump into an existing codebase, understand it, and extend it. - Clear communication skills and comfort working across time zones. Requirements - AWS experience (S3, EC2, ECS, or similar). - Experience consuming and integrating REST APIs at scale. - Docker and containerisation experience. - MLOps experience including CI/CD and model monitoring. - Familiarity with geospatial or aerial imagery data. - Experience with pipeline orchestration tools like Ray, Kubeflow, or Flyte. Benefits - 4 extra "YOU" days off each year—take a break, no questions asked! - Company-sponsored volunteering days to give back. - Generous parental leave policies for growing families. - Work from Overseas Policy - explore the world in the approved list of cities while you work! - Access to LinkedIn Learning for continuous growth. - Discounted Private Health Insurance plans. - Monthly wellbeing and technology allowance. - A Nearmap subscription (naturally!).

Role Description - Writing effective, scalable code. - Knowledge of OpenCV. - Knowledge of machine learning libraries e.g. Tensorflow, Keras, Numpy, Matplotlib, Pandas, Dask etc. - Knowledge of data analysis in Python, Predictive analysis, Correlation, Regression, Factor Analysis, NLP etc. - Knowledge of data modelling, categorisation. - Knowledge of image classification, object detection, recommending system. Qualifications - 5+ years of experience as Python Developer/Python Engineer. - Strong Problem solving ability. - Experience handling gigabyte and terabyte size datasets. - You are & remain aware of the latest tools and technologies. - Experience working with retail or e-commerce data. - Experience in Python scripting. - Object-oriented programming skills. - Experience with version control systems (Git). - Experience deploying machine learning models.

FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers, advertisers, and media buyers. Powered by premium video content, robust data, and advanced technology, we're making it easier for buyers and sellers to transact across all screens, data types, and sales channels. As a global company, we have offices in nine countries and can insert advertisements around the world. Job Summary The Machine Learning Revenue (MLR) Architect is a senior leadership role responsible for leading and coordinating the strategic development of MLR solutions. This position requires a blend of business understanding, critical thinking skills along with expertise in Machine Learning (ML) methodologies, business process and systems architecture design. Key duties include designing how algorithms embed within broader systems, leading engineers, data scientists and analysts, and collaborating with business stakeholders to ensure efforts drive economic growth. Job Description - Opportunity Definition Work with business and operational teams to understand the problem, the operational and system constraints, the available data, and decision points. Communicate this to the team to ensure team members have a clear understanding of the problem. Define how opportunities fit within the long-term evolution of the systems. - Define Project KPIs and Analytics Strategies : Based on the problem and the - available data, determine how we can measure success and monitor system - outcomes/dynamics. - Solutions design: Define and drive the evolution of the solution, identifying points of high leverage, and phases/evolution of the system. Determine whether and how 3rd party capabilities can be integrated into the solution. Solutions may include changes to data, operational processes, and software systems. - Project stewardship: Evolve plans and direction as we iteratively gather feedback and learn about solution effectiveness. Identify and resolve roadblocks, miscommunication, and misunderstanding, and, as needed, adapt plans to meet target timelines. - Stakeholder management: Collaborate with cross-functional leaders to identify opportunities, communicate and evaluate solutions, and gather feedback. - Team leadership: Mentor of data scientists and analysts, fostering a collaborative and high-performing environment. Passionate about solving problems, and inspires similar spirit in team members. - Technical direction: Provide technical guidance, set standards, and ensure the team uses appropriate tools and methodologies. - Innovation: Stay current with emerging trends in data science, AI, and big data - technologies to drive innovation and maintain a competitive advantage. - Consistent exercise of independent judgment and discretion in matters of significance. - Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary. - Other duties and responsibilities as assigned. Required skills and qualifications - Education: A Master's or PhD in a quantitative field such as Management Science, Computational Economics, Statistics, or Computer Science, or equivalent industry experience. - Experience: Extensive experience in Advertising Technology, with a proven track record of delivering business results. - Business acumen: Strong understanding of how math can be leveraged to solve business problems and drive growth. Strong understanding of digital advertising - ecosystem and technologies. Exceptional problem-solving and critical thinking skills. - Technical proficiency: Strong expertise in statistical analysis, machine learning, data mining, and data visualization. - Programming: Proficiency in languages like Python or R, and experience integrating solution into the enterprise infrastructure - Big data: Experience with big data technologies such as Hadoop and Spark. - Leadership: Proven experience in leading and managing teams of technical professionals - Communication: Excellent communication and presentation skills to translate complex data into actionable business strategies for various audiences. Employees at all levels are expected to: - Understand our Operating Principles; make them the guidelines for how you do your job. - Own the customer experience think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services. - Know your stuff be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences. - Win as a team make big things happen by working together and being open to new ideas. - Be an active part of the Net Promoter System a way of working that brings more employee and customer feedback into the company by joining huddles, making call backs and helping us elevate opportunities to do better for our customers. - Drive results and growth. - Support a culture of inclusion in how you work and lead. - Do what's right for each other, our customers, investors and our communities. Disclaimer: This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications. Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Comcast will consider for employment applicants with arrest or conviction records in accordance with the requirements of applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Please note that federal state, or local laws and regulations may restrict or prohibit Comcast from hiring individuals convicted of certain crimes. Additionally, an applicant's criminal history may have a direct, adverse, and negative relationship on the job duties of this position, which may result in the withdrawal of a conditional offer of employment. Skills: Leadership; Mathematics Modeling; Critical Thinking; Analytics Salary: National Pay Range: $192,396.16 USD-$450,928.49 USD Illinois Pay Range: $204,420.92 USD - $396,817.07 USD Colorado Pay Range: $216,445.68 USD - $414,854.21 USD Hawaii Pay Range: $252,519.96 USD - $378,779.93 USD Washington DC Pay Range: $276,569.48 USD - $414,854.21 USD Maryland Pay Range: $228,470.44 USD - $414,854.21 USD Minnesota Pay Range: $216,445.68 USD - $378,779.93 USD New York Pay Range: $228,470.44 USD - $450,928.49 USD Washington Pay Range: $216,445.68 USD - $432,891.35 USD New Jersey Pay Range: $240,495.20 USD - $432,891.35 USD Vermont Pay Range: $228,470.44 USD - $360,742.79 USD Massachusetts Pay Range: $240,495.20 USD - $432,891.35 USD California Pay Range: $216,445.68 USD - $400,825.32 Comcast intends to offer the selected candidate base pay within this range, dependent on job-related, non-discriminatory factors such as experience. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That's why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality - to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 15 Years +

• Design, train, and evaluate predictive ML models with a focus on forecasting and time-series applications • Conduct exploratory data analysis, feature engineering, and statistical modeling across large structured and unstructured datasets • Collaborate with Engineering to define ML infrastructure requirements, and deploy and integrate ML models into operational workflows and decision-support tools • Work cross-functionally with Camus teams to define problem statements and translate business objectives into ML solutions • Communicate model performance, uncertainty, and limitations clearly to both technical and non-technical audiences • Champion ML best practices around reproducibility, versioning, and testing