This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role supports high-impact collaborations with leading AI teams focused on improving how conversational AI models reason about complex engineering concepts across multiple disciplines. - Write and refine prompts that guide AI models in engineering-related scenarios - Evaluate AI-generated responses for technical accuracy and applied reasoning - Verify engineering claims using domain expertise and authoritative sources - Annotate responses by identifying strengths, gaps, and conceptual inaccuracies - Assess clarity, structure, and appropriateness of explanations for different audiences - Apply structured evaluation guidelines and benchmarking standards - Ensure model responses align with expected system behavior and engineering logic Qualifications - PhD in Engineering or a closely related technical discipline - Expertise in one or more of the following areas: - Mechanical & Physical Systems Engineering - Electrical, Electronic & Computer Engineering - Chemical, Materials & Process Engineering - Civil, Environmental & Infrastructure Engineering - Strong experience using large language models (LLMs) - Excellent technical writing and explanation skills - Strong analytical reasoning and attention to detail - Ability to identify subtle technical inaccuracies in model outputs Requirements - Applied research or industry engineering experience - Experience with RLHF, model evaluation, or AI data annotation - Experience teaching or mentoring technical concepts - Familiarity with evaluation rubrics or structured review frameworks What Success Looks Like - Identifying technical inaccuracies or flawed reasoning in engineering outputs - Improving the rigor and clarity of AI explanations - Producing consistent evaluation artifacts that strengthen model performance - Helping ensure AI systems provide reliable engineering guidance Why This Opportunity - Contribute directly to improving the reasoning capabilities of advanced AI systems - Apply deep engineering expertise to real-world AI development - Work with cutting-edge AI labs and research teams - Flexible remote work with competitive compensation Contract Details - Independent contractor role - Fully remote with flexible scheduling - Compensation: $73.29/hr - Weekly payments via Stripe or Wise - Projects may expand depending on performance and project needs About the Platform This opportunity is available through a leading AI-driven work platform.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role focuses on designing, implementing, and operationalizing AI systems with a strong emphasis on structured evaluation, measurable quality, and production-grade reliability. - Build and maintain evaluation frameworks (LLM-as-Judge, rubric-based scoring, regression test suites) to measure output quality, reliability, and drift. - Architect and implement multi-agent workflows with clear coordination, tool usage, and failure handling patterns. - Build structured observability into AI systems (tracing, prompt/version tracking, evaluation logging, cost and latency monitoring). - Define and enforce quality gates for AI features using automated evaluations prior to production release. - Optimize inference performance (latency, token usage, caching, batching, routing across models). - Collaborate with product and engineering teams to translate business requirements into testable AI system designs. - Contribute to code reviews, architectural discussions, and internal standards for AI development. - Design and implement Retrieval-Augmented Generation (RAG) systems and Model Context Protocol (MCP) servers using structured and unstructured enterprise data. - Develop and manage fine-tuning workflows (SFT, preference optimization, or related techniques) including dataset preparation, versioning, and validation. Qualifications - 3-5 years of full stack engineering experience with strong fundamentals in object-oriented programming, applicable design patterns, and AI-focused system design. - Professional experience in Python, C#, Java, or a similar language used in production systems. - Experience with LLM evaluation and observability tooling (e.g. Langfuse, LangSmith, OpenTelemetry-based tracing, custom evaluation harnesses). - Experience implementing guardrails, policy enforcement, and safety layers in AI-driven systems while leveraging LLM-as-Judge for validation and continuous improvement. Requirements - Familiarity with performance optimization techniques for LLM-based systems (latency, caching, routing, batching). - Experience building production-grade RAG systems (retrieval pipelines, chunking strategies, embeddings, reranking, context construction). - Experience contributing to internal AI standards, reusable frameworks, or platform-level tooling. - Experience deploying AI systems in cloud environments (AWS, Azure, GCP). - Experience in Databricks (model serving endpoints, ML Flow). Company Description Risepoint is an education technology company that provides world-class support and trusted expertise to more than 100 universities and colleges. We primarily work with regional universities, helping them develop and grow their high-ROI, workforce-focused online degree programs in critical areas such as nursing, teaching, business, and public service. Risepoint is dedicated to increasing access to affordable education so that more students, especially working adults, can improve their careers and meet employer and community needs.

Requisition Number: 2348718 Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. We're seeking a visionary AI/ML Lead to drive innovation in IT Operations through intelligent automation, predictive analytics, and agentic AI. This role will lead the design and deployment of scalable machine learning systems that enhance observability, accelerate incident response, and enable self-healing infrastructure across the enterprise. 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: - AI/ML Technical Leadership: Lead the design and delivery of enterprise scale AI/ML capabilities for IT operations, including predictive analytics, intelligent automation, and autonomous remediation - Data & Platform Engineering: Architect and oversee robust, scalable data pipelines ingesting structured and unstructured data from observability and ITSM platforms (e.g., Splunk, Dynatrace, ServiceNow, logs, metrics, traces) - Feature Engineering & Model Enablement: Define and govern high quality feature frameworks supporting anomaly detection, predictive alerting, capacity forecasting, and operational intelligence use cases - Model Operationalization: Partner with data scientists and platform teams to operationalize ML models, ensuring production readiness across performance, scalability, reliability, and maintainability - AI Driven Automation: Integrate ML and AI insights into orchestration and automation platforms (e.g., Jenkins, Interlink) to enable closed loop, self healing operational workflows - Agentic AI Systems: Design and guide the implementation of agentic AI solutions capable of reasoning, planning, and executing actions across IT operations, including incident triage, root cause analysis, and resolution - MLOps & Governance: Establish and enforce MLOps standards, model lifecycle management, and data governance practices aligned with enterprise security, privacy, and compliance requirements - Cloud & Infrastructure Enablement: Leverage cloud native and hybrid architectures to support real time analytics, scalable model inference, and resilient AI platforms - Cross Functional Collaboration: Collaborate with engineering, operations, security, and business stakeholders to define requirements, document architectures, and contribute reusable patterns for AI driven operations - Responsible AI: Translate emerging AI research into production ready capabilities while embedding ethical AI principles, including fairness, transparency, explainability, and accountability, throughout the lifecycle 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 in Computer Science, Data Science, Engineering, or a related field and equivalent advanced practical experience or higher in Computer Science, Data Science, Engineering, or a related field (or equivalent practical experience) - 6+ years of experience building and deploying AI/ML solutions in enterprise production environments - 5+ years of experience applying ML to IT operations, infrastructure, reliability engineering, or observability domains - 5+ years of experience in Python and SQL, with hands on experience using distributed data processing frameworks such as Spark - 5+ years of experience with cloud platforms (Azure, AWS, or GCP), including hybrid and cloud native architectures - 5+ years of experience implementing MLOps practices, CI/CD pipelines, model monitoring, and lifecycle management - 3+ years of experience with NLP, Large Language Models (LLMs), Generative AI, and modern AI frameworks - 2+ years of experience with containerization and orchestration technologies such as Docker and Kubernetes - 2+ years of experience leading complex technical initiatives and influence architecture and platform decisions across teams Preferred Qualifications: - Hands-on experience designing and deploying agentic or autonomous AI systems in operational contexts - Experience leading AI/ML initiatives, mentoring engineers or data scientists, and setting technical direction - Experience in healthcare, regulated industries, or large scale enterprise platforms - Proven experience working in agile, product driven environments delivering scalable, high impact solutions - Solid understanding of IT operations concepts, including incident management, CMDB, monitoring, alerting, and reliability engineering - Familiarity with Responsible AI and governance frameworks, including fairness, transparency, and explainability - Proven solid technical communication skills, including the ability to explain complex AI concepts to senior and non technical stakeholders *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. #OptumTechPJ

• Architect and implement GenAI and LLM‑based systems, including fine‑tuning, evaluation, and optimization • Build scalable pipelines for data processing, model training, inference, and continuous improvement • Deploy and manage AI workloads across AWS, Azure, or GCP using cloud‑native services • Integrate embeddings, vector search, and RAG pipelines into production environments • Optimize GPU/accelerator utilization for distributed training and high‑performance inference • Develop automation for CI/CD, MLOps, observability, and model lifecycle management • Ensure cloud security, compliance, and cost‑efficient resource allocation • Evaluate emerging AI frameworks, tools, and cloud services to drive innovation • Partner with cross‑functional teams to translate business needs into technical solutions