• Develop and improve TTS / Voice Generation models • Train, fine-tune, and evaluate speech models • Bring research ideas into production systems • Work across research, engineering, and product • Help define technical direction and ML best practices • Drive execution in a fast-changing environment • Collaborate closely with engineering, product, and business stakeholders

Role Description Consistent with and supportive of CTU's mission (to provide industry-relevant higher education to a diverse student population through innovative technology and experienced faculty, enabling the pursuit of personal and professional goals), Adjunct Faculty members provide quality and innovative instruction and meaningful engagement with our students to successfully achieve the relevant course, program, and degree level outcomes and support their academic success. - Prepare relevant, insightful, and engaging instructional materials and utilize existing course materials that support learning by CTU's student population. - Provide instruction in assigned courses (including applicable laboratory or work that is integral to the courses) that aligns with CTU's curricula and outcomes, instructional modalities, course technologies, and faculty expectations. - Engage and communicate with students to encourage their course participation and learning while maintaining mutual respect and professionalism. - Relate professional/industry experience to CTU's Professional Learning Model by the continuation of professional/technical skills development, introduction of professional/industry perspectives into courses, and active awareness of professional/industry trends and opportunities. - Maintain accessibility for and provide timely responsiveness to students, academic/faculty leadership, and University staff by telephone, CTU e-mail, and other appropriate means of communication. - Establish and maintain weekly office hours for student questions/support. - Assess student performance on course assignments and provide assignment feedback to support continued student growth and development. - Maintain appropriate documentation of student course activities. - Work with appropriate CTU teams (e.g., advising, academic/faculty leadership, and University staff) and leverage appropriate information to identify and support students who may be exceptional or challenged in their coursework and/or educational endeavors. - Refer students to appropriate co-curricular and extra-curricular resources (e.g., advising, tutoring, library, learning centers, and career services). - Participate in and contribute to CTU's academic governance through attendance at appropriate University/college/program meetings and participation in the academic assessment and institutional effectiveness process (including completion of appropriate surveys and participation in continuous improvement initiatives). - Successfully complete required new faculty certification training, course-specific technology/pedagogical training, annual ethics and information technology policy training, and annual faculty development requirements. - Provide periodic required documentation of ongoing and updated licensures, certifications, immunizations (as appropriate to the specific college/program), scholarship, and academic/professional experience (e.g., CVs/resumes). - Work closely with Program Chair and/or Lead Faculty (as appropriate). - Perform other responsibilities and abide by the appropriate policies and procedures contained in CTU's Faculty Handbook. Qualifications - Strong organizational and time management skills, with proficiency in meeting deadlines and urgency in responding to questions/requests. - Strong interpersonal and oral presentation/written communication skills. - Proficiency in working effectively, cooperatively, and flexibly in a team environment. - Proficiency with standard office and mobile applications (i.e., word processing, presentations, e-mail, calendaring, teleconferencing, text messaging, personal computers, and smart phones/tablets). Requirements - A Master’s or PhD degree in Computer Science, or Electrical Engineering, or Computer Engineering. - Deep Knowledge of GPU Architecture: In-depth understanding of GPU architecture, including parallel computing, memory management, and performance optimization. - Experience with NVIDIA Technologies: Familiarity with NVIDIA technologies such as CUDA, TensorRT, and other tools and frameworks provided by NVIDIA. - Practical experience in the industry, particularly in roles involving GPU programming, AI, and machine learning applications. - Previous teaching experience at the university level, especially in courses related to computer architecture, parallel computing, or AI. - Strong verbal and written communication skills to effectively convey complex concepts to students. - Curriculum Development: Ability to develop and update course materials, including lectures, assignments, and exams, to keep pace with advancements in GPU technology and AI. - Research Contributions: Active involvement in research, particularly in areas related to GPU architecture and AI, can be a plus. - NVIDIA Certification: Certification from NVIDIA, such as becoming an NVIDIA-Certified Instructor, can be highly beneficial. This certification demonstrates proficiency in NVIDIA technologies and the ability to teach them effectively.

Role Description Consistent with and supportive of CTU's mission (to provide industry-relevant higher education to a diverse student population through innovative technology and experienced faculty, enabling the pursuit of personal and professional goals), Adjunct Faculty members provide quality and innovative instruction and meaningful engagement with our students to successfully achieve the relevant course, program, and degree level outcomes and support their academic success. - Prepare relevant, insightful, and engaging instructional materials and utilize existing course materials that support learning by CTU's student population. - Provide instruction in assigned courses (including applicable laboratory or work that is integral to the courses) that aligns with CTU's curricula and outcomes, instructional modalities, course technologies, and faculty expectations. - Engage and communicate with students to encourage their course participation and learning while maintaining mutual respect and professionalism. - Relate professional/industry experience to CTU's Professional Learning Model by the continuation of professional/technical skills development, introduction of professional/industry perspectives into courses, and active awareness of professional/industry trends and opportunities. - Maintain accessibility for and provide timely responsiveness to students, academic/faculty leadership, and University staff by telephone, CTU e-mail, and other appropriate means of communication. - Establish and maintain weekly office hours for student questions/support. - Assess student performance on course assignments and provide assignment feedback to support continued student growth and development. - Maintain appropriate documentation of student course activities. - Work with appropriate CTU teams (e.g., advising, academic/faculty leadership, and University staff) and leverage appropriate information to identify and support students who may be exceptional or challenged in their coursework and/or educational endeavors. - Refer students to appropriate co-curricular and extra-curricular resources (e.g., advising, tutoring, library, learning centers, and career services). - Participate in and contribute to CTU's academic governance through attendance at appropriate University/college/program meetings and participation in the academic assessment and institutional effectiveness process (including completion of appropriate surveys and participation in continuous improvement initiatives). - Successfully complete required new faculty certification training, course-specific technology/pedagogical training, annual ethics and information technology policy training, and annual faculty development requirements. - Provide periodic required documentation of ongoing and updated licensures, certifications, immunizations (as appropriate to the specific college/program), scholarship, and academic/professional experience (e.g., CVs/resumes). - Work closely with Program Chair and/or Lead Faculty (as appropriate). - Perform other responsibilities and abide by the appropriate policies and procedures contained in CTU's Faculty Handbook. Qualifications - Strong organizational and time management skills, with proficiency in meeting deadlines and urgency in responding to questions/requests. - Strong interpersonal and oral presentation/written communication skills. - Proficiency in working effectively, cooperatively, and flexibly in a team environment. - Proficiency with standard office and mobile applications (i.e., word processing, presentations, e-mail, calendaring, teleconferencing, text messaging, personal computers, and smart phones/tablets). Requirements - A Master’s or PhD degree in Computer Science, or Electrical Engineering, or Computer Engineering. - Deep Knowledge of GPU Architecture: In-depth understanding of GPU architecture, including parallel computing, memory management, and performance optimization. - Experience with NVIDIA Technologies: Familiarity with NVIDIA technologies such as CUDA, TensorRT, and other tools and frameworks provided by NVIDIA. - Practical experience in the industry, particularly in roles involving GPU programming, AI, and machine learning applications. - Previous teaching experience at the university level, especially in courses related to computer architecture, parallel computing, or AI. - Strong verbal and written communication skills to effectively convey complex concepts to students. - Curriculum Development: Ability to develop and update course materials, including lectures, assignments, and exams, to keep pace with advancements in GPU technology and AI. - Research Contributions: Active involvement in research, particularly in areas related to GPU architecture and AI, can be a plus. - NVIDIA Certification: Certification from NVIDIA, such as becoming an NVIDIA-Certified Instructor, can be highly beneficial. This certification demonstrates proficiency in NVIDIA technologies and the ability to teach them effectively.

Requisition Number: 2352352 Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. The Enterprise Information Security (EIS) team is responsible for cybersecurity across our organization. We support our business and members by reducing risk, rapidly responding to threats, focusing on business resiliency and securing new acquisitions. The Principal AI / Machine Learning Data Engineer role focuses on designing and building scalable data platforms that enable advanced analytics, machine learning, and AI-driven solutions. This role will support the development of intelligent systems that process large-scale event and operational data, enabling faster insights, automation, and decision-making across the organization. This position sits at the intersection of data engineering, machine learning, and AI, with an emphasis on building modern data pipelines and enabling production-grade AI capabilities. Ideal Candidate Profile: - Demonstrated experience building and operating production data platforms and pipelines across batch and streaming workloads - Solid hands-on engineering in Python and SQL; familiarity with JVM languages (Java/Scala) in Spark ecosystems is a plus - Experience with distributed processing and lakehouse/warehouse patterns (eg, Spark/PySpark, Databricks, Snowflake) - Experience building ingestion frameworks for structured and unstructured data, including event/log and semi-structured formats - Experience enabling Generative AI solutions in production (eg, RAG-style architectures), including retrieval patterns and evaluation/monitoring practices - Familiarity with knowledge-centric data approaches (eg, metadata-driven systems, entity resolution, and/or graph concepts) to improve discoverability and downstream analytics - Solid data quality, observability, and monitoring mindset (profiling, validation, alerting, and reliability improvements) - Comfort with orchestration, CI/CD, containerization, and infrastructure-as-code (eg, Airflow, GitHub Actions, Docker, Terraform, Kubernetes) - Cloud experience (AWS, Azure, and/or GCP), including secure handling of sensitive data (PII/PHI) and collaboration with compliance partners - Ability to lead through influence, mentor engineers, and translate ambiguous problems into scalable technical roadmaps You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: - Design, develop, and maintain scalable data pipelines and data platforms supporting analytics, machine learning, and AI use cases - Build and optimize ingestion frameworks for large-scale structured and unstructured data, including streaming and event-driven sources - Partner with cross-functional stakeholders to understand evolving data and AI needs and define long-term technical solutions - Enable and support machine learning and AI workflows, including feature engineering, data preparation, and model deployment support - Drive strategic initiatives around Generative AI, data quality, observability, lineage, and governance - Develop and maintain frameworks that support rapid experimentation and deployment of AI/ML solutions - Introduce and evolve best practices in data modeling, orchestration, testing, and monitoring - Identify and champion opportunities for platform scalability, performance optimization, and cost efficiency - Collaborate with product, analytics, and infrastructure teams to deliver high-impact data and AI solutions - Build and maintain reusable parsing, enrichment, analytic, and service libraries to accelerate delivery across teams - Work comfortably under time-sensitive conditions while ensuring thoroughness - Maintain high ethical standards and the ability to remain objective and confidential You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - Bachelor's degree or equivalent experience - 5+ years of experience designing, building, and operating production data pipelines and platforms - 5+ years of hands-on development with Python (preferred) and/or Java, including code reviews, packaging, and deployment - 5+ years of experience with Spark (PySpark) and Databricks (or similar distributed data processing platform) - 2+ years of experience leveraging and deploying Generative AI use cases to production environments - Solid SQL skills and experience working with data lakes and warehouses (e.g., Databricks, Snowflake) - Experience building ingestion frameworks for structured and unstructured data (e.g., event/log, semi-structured JSON), including parsing and enrichment patterns - Experience designing and scaling ELT/ETL frameworks with orchestration tools such as Airflow (or equivalent) - Experience implementing data quality, observability, and monitoring practices (e.g., data quality checks, pipeline SLAs/SLOs, alerting) - Experience with metadata, lineage, and governance concepts and tooling (e.g., data catalogs, lineage, access controls) - Experience with data modeling best practices for analytics and ML use cases - Experience with DevOps and CI/CD practices and tools (e.g., GitHub Actions), containerization, and infrastructure-as-code (e.g., Docker, Kubernetes, Terraform) - Experience supporting ML/AI workflows (feature engineering, data preparation, and model deployment enablement); exposure to MLOps practices is a plus - Demonstrated ability to partner with cross-functional stakeholders, translate requirements into technical solutions, and lead through influence Preferred Qualifications: - Experience with cloud platforms such as AWS, Azure, or Google Cloud, including managed data services - Experience with streaming and event-driven architectures (e.g., Kafka, Kinesis, Event Hubs) - Experience with data quality and validation frameworks (e.g., Great Expectations, Deequ) and/or data observability tooling - Experience enabling MLOps practices (e.g., feature stores, model registries, experiment tracking, deployment automation) - Experience with lakehouse architectures, Delta Lake, and advanced Spark optimization/performance tuning - Experience with data visualization tools and libraries such as Plotly, seaborn, and Chartjs - Experience with machine learning and predictive analytics - Familiarity with security and privacy concepts for data platforms (e.g., least privilege, PII/PHI handling) and working with compliance partners *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment. #BI-Hybrid