This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role offers the opportunity to shape and scale the next generation of data infrastructure and machine learning systems that power customer-facing products and business insights. The Senior Data/ML Engineer will design, implement, and optimize core data pipelines, ML workflows, and analytics platforms to deliver high-quality, reliable, and actionable data. You will work closely with product, engineering, and analytics teams to operationalize ML models, automate workflows, and ensure data quality and governance at scale. The position combines hands-on technical expertise with strategic influence, making it ideal for engineers passionate about solving complex data challenges and building impactful ML-driven solutions. Collaboration across global teams and ownership of scalable, customer-focused data products are central to this role. - Design, build, and maintain core data models supporting analytics, machine learning, and generative AI workloads. - Implement automation and operationalize ML model workflows to improve efficiency and reduce manual processes. - Collaborate with engineering, product, and analytics teams to deliver seamless customer-facing data products and integrations. - Establish and maintain data quality, observability, and governance frameworks to ensure reliable data at scale. - Document data flows, integration contracts, and operational runbooks for efficient scaling and knowledge sharing. - Develop solutions leveraging modern ML technologies, including LLMs, embeddings, recommendations, and forecasting models. Qualifications - 5+ years of experience in data engineering, with hands-on exposure to machine learning, MLOps, or backend workflow automation. - Proficiency in SQL and Python, with experience using ML frameworks and libraries. - Deep expertise in modern data stack tools such as dbt, Snowflake, and Looker/Omni; experience with Kafka or Flink is a plus. - Strong understanding of semantic layer design, dimensional modeling, and data architecture best practices. - Knowledge of data governance, data quality, observability, and security/analytics best practices. - Experience building products with generative AI, LLMs, embeddings, or advanced ML techniques. - Excellent problem-solving, communication, and collaboration skills for working across global, cross-functional teams. Benefits - Competitive base salary: $151,000 – $205,000 depending on location, plus potential variable compensation. - Equity participation in the company. - 401(k) match, medical, dental, vision, and life insurance coverage. - Fully remote work with monthly home office stipend. - Flexible vacation and paid time off policy. - Family planning resources and specialized employee support programs. - Learning and development program for professional growth in market-focused areas.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description DeVry University focuses on developing long-term relationships with superior instructors who have high professional standards, excellent communication skills, enthusiasm, and a commitment to providing the finest practitioner-focused education. We are seeking primarily Industry Professionals to share their knowledge and experience with undergraduate and graduate students in a variety of fields. - Courses meet once or twice a week for eight weeks. - Face-to-face interaction is blended with technology (such as online discussions and online assignments) for an enhanced learning environment. - Faculty are responsible for facilitating student learning by teaching educational courses and programs in accordance with DeVry University requirements. - Faculty develop course syllabi and lesson plans and apply teaching techniques to best achieve course and programmatic objectives. - All DeVry instructors will participate in a comprehensive faculty training program and ongoing faculty development activities to ensure the highest quality instruction. - DeVry University does not guarantee any specific number of work hours or assignments, which may vary based on the University’s needs and discretion. Responsibilities - Develops and provides students with an approved DeVry University syllabus that follows a template established by the local campus, and which includes the terminal course objectives. - Organizes, prepares, and regularly revises and updates all course materials. - Uses appropriate technological options for online technologies and course-related software, including Websites, e-mail, and online discussions for preparing the course and making it accessible to students. - Models effective oral and written communications that engage the students, provide clarity, and improve student learning. - Sets clear expectations for the course by publishing course terminal objectives, assignment/examinations dates, and weight the distribution of various evaluation categories. - Ensures that the content and level of material included on exams correspond to the course terminal objectives. - Demonstrates consistency and fairness in the preparation and grading of exams, and provides timely feedback to students. - Completes other duties as assigned. Qualifications - A master's degree is required for all faculty positions (with 18 graduate hours in the subject being taught for undergraduate teaching; MSME, MSEE, MSSE, MSCS). - Machine Learning/AE background required. - Qualifying credentials must be awarded by an institution accredited by an agency recognized by the U.S. Department of Education or the Council for Higher Education Administration, or by an international institution determined to hold equivalent accreditation. - Additional requirements driven by state licensing or accreditation considerations may apply. - Faculty must have requisite subject matter expertise and outstanding communication skills. Pay - Visiting Professor pay is based on degree, credit hours taught per 8-week session, and location. - Pay may vary in most states from $1500-$2700 per 8-week session. - Pay in the states of AZ, CA, IN, and PA is paid at an hourly rate of either $22.00/hour or $23.50/hour. Benefits - 401(k) and Roth Plan. - Paid Tuition Program. - Remote and Flex Work Options. - Paid Sick Time. - Technology Stipend. - Benefits vary based on employment status. Part-time/Visiting Professors positions may not be eligible for all benefits.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Peer Mentor, you will work part-time helping students transition to SNHU and make the most out of their first-year experience (FYE). You will report to the Associate Dean. Peer Mentors provide personalized mentoring to first-year students in addition to delivering and supporting programming designed to support engagement and success of at-risk non-traditional students. Peer Mentors connect with students inside the student learning community with virtual one-on-one and group mentorship and (whenever possible) at local, regional meet-up events. Peer Mentors hold regular office hours during which they provide both synchronous and asynchronous assistance to students. Peer Mentors may work up to 20 hours a week. We are a remote friendly working environment. - Hold real-time office hours throughout the term for mentoring appointments - Provide one-on-one and group mentorship to first-year students enrolled at SNHU - Be active (e.g., posting responses, responding to chats) in the Learning Community or activities related to the Learning Community (e.g. webinars) according to set standards - Engage students through delivery of online webinars or programming - Maintain confidentiality - Discuss any mentee concerns with the peer mentor supervisor - Understand and abide by all SNHU policies - Attend and participate in all training sessions and meetings - Reflect the culture and values of SNHU Qualifications - 1+ years of experience using social media and using virtual meeting or conference software - Access to a personal computer and reliable internet connection - SNHU current or previous students preferred Compensation The hourly pay range for this position is $15.87 - $25.41. Actual offer will be based on skills, qualifications, experience and internal equity, in addition to relevant business considerations. We expect this position to be hired in the following target hiring range $17.54 - $23.74.

About the Role In this role you will support cross-functional teams in designing and implementing machine learning-based solutions and contribute to Machine Learning Engineering (MLE) internal tools and best practices. What You’ll Do - Work with Engineers to integrate Data Science models into customer-facing solutions - Support model development through Google Cloud Platform (GCP) service enablement and configuration - Contribute to the roadmap for Data Science and MLE team tools and technology development - Design and implement monitoring and alerting systems to maintain model performance and integrity - Work within the Machine Learning Engineering team to develop leverageable toolsets to standardize and streamline model implementations - Mentor and guide junior machine learning engineers, providing technical expertise and fostering a culture of continuous learning and development - Think in terms of iterative development, document, and communicate throughout the products' data science lifecycle - Work closely with Data Scientists to efficiently scale Extract Transform Load (ETL) workflows and models to meet production requirements - Optimize and fine-tune models to achieve peak performance and accuracy within resource constraints - Stay up-to-date on GCP services and best practices for Data Science and Machine Learning implementations - Additional tasks may be assigned What Skills You Have Required - Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field - 3+ years of progressively complex Data Science or analytics experience - 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery - In-depth knowledge of Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc - Extensive expertise with CI/CD and IaC best practices - Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL - Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) - Experience with Agile/XP software development - Experience with OGSM approach; strategy development, and execution Preferred - Master’s Degree and/or Ph.D. - Proficiency in Java/Scala or other languages - Retail experience - E-commerce experience