Role Description In this role, you will collaborate on AI-focused projects involving reasoning, problem-solving, data interpretation, and scientific explanation development. You will also contribute to building evaluation benchmarks for advanced Biology topics ranging from undergraduate to PhD-level concepts. - Design and solve challenging Biology problems for AI model evaluation - Create clear, step-by-step solutions with strong scientific reasoning - Collaborate with researchers to improve AI model performance - Contribute to benchmark creation for Biology curricula - Analyze areas where language models struggle, including abstraction and multi-step reasoning - Provide detailed annotations and constructive feedback Qualifications - Master’s degree, Ph.D., Postdoctoral degree, or currently pursuing advanced studies in: - Biology - Biotechnology - Biochemistry - Related fields - Strong research and analytical skills - Excellent English comprehension and communication skills - Ability to work independently in a remote environment - Reliable desktop/laptop and internet connection - Availability for 40 hours/week with at least 4 hours PST overlap Requirements - Candidates should be proficient in at least three of the following tools: - BWA - Bowtie2 - GATK - HMMER - HHsuite - STAR - SPAdes - IQ-TREE - OpenMM - AlphaFold2 - PyOpenMS - RELION - PhysiCell - COPASI - Comet - COBRApy - Hifiasm - ABySS - DeepVariant - Flye - OR-Tools - Bracken - Kraken2 - MEGAHIT - antiSMASH - BEAST2 - FastTree - DIA-NN - Percolator - AutoDock Vina - CP2K - Salmon - MethylDackel - Canu - GROMACS Additional Notes - LinkedIn profile must be included in the resume - Candidates will undergo a background verification after onboarding - Work allocation begins only after successful verification - This is a freelance/contractor engagement with no medical or paid leave benefits Benefits - Fully remote work setup - Opportunity to work on cutting-edge AI projects - Collaborate with leading LLM research teams - Potential contract extension based on performance

Requisition Number: 2360260 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 inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. We are looking for an AI/ML Engineer to build and enhance conversational AI solutions for voice, IVR, and chatbot platforms. The role involves developing NLP pipelines, integrating LLMs (e.g., Amazon Bedrock or OpenAI), and applying effective prompt engineering and evaluation techniques to improve conversational quality. You will work with AWS-native services such as Lambda, API Gateway, DynamoDB, and event-driven architectures, and contribute to solutions using Amazon Connect and Amazon Lex (V2). The position requires close collaboration with engineering teams to deliver scalable, reliable, and secure production systems, while continuously monitoring performance and improving AI models based on real-world data. 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 deploy AI-powered solutions, specifically voice-based IVR and conversational interfaces, to address complex business challenges - Integrate Large Language Models (LLMs) like Bedrock or OpenAI into production environments using prompt engineering and evaluation techniques - Build and maintain robust backend services and integrations using AWS Lambda, API Gateway, and DynamoDB - Develop real-time orchestration and event-processing systems within microservices and event-driven architectures - Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement - Evaluate emerging trends in AI/ML and NLP to inform solution design and drive strategic innovation - Ensure all AI solutions are developed and deployed with an emphasis on the responsible use of AI and data privacy - Collaborate with cross-functional teams to monitor and optimize AI system performance and observability 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: - Undergraduate degree or 4+ years of equivalent software engineering experience - 4+ years of experience in software engineering specifically focused on AI/ML systems - 2+ years of experience with Amazon Connect, including Contact Flows, routing, and integrations - 2+ years of experience with Amazon Lex (V2) for building conversational interfaces - 2+ years of experience with Python or Java for backend and AI service development - 2+ years of experience with AWS core services: Lambda, API Gateway, and DynamoDB - 2+ years of experience building and deploying voice-based or IVR systems Preferred Qualifications: - Experience with event-driven and microservices architectures - Knowledge of CI/CD pipelines and automated testing for AI/ML applications - Solid understanding of Natural Language Processing (NLP) techniques and Large Language Models (LLMs) - Familiarity with AI system monitoring, observability, and real-time performance tuning - Proven expertise in prompt engineering and AI model evaluation frameworks *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 $72,800 to $130,000 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.

Role Description UP.Labs is seeking a Sr. AI/ML Engineer to help build applied AI systems across computer vision, LLM-powered workflows, intelligent automation, and production AI infrastructure. This role is best suited for someone who is comfortable operating in early-stage, ambiguous environments. - You’ll work on AI-driven applications involving image detection, object recognition, intelligent automation, and LLM-powered workflows. - One key product area involves using computer vision models to identify industrial objects, human interactions, defects, and operational patterns in manufacturing environments. - You’ll also build LLM-based capabilities using modern orchestration frameworks, retrieval systems, tool-calling patterns, and agentic workflows. - The work will often involve incomplete data, evolving requirements, and open-ended technical decisions. - This is a highly collaborative role, but not a heavily prescribed one. - You’ll be expected to bring technical judgment, ownership, and initiative to ambiguous problems. What You’ll Do - Design, train, evaluate, and deploy machine learning models for real-world applications. - Build and improve computer vision pipelines for object detection, classification, and image understanding. - Build LLM-powered features, agentic workflows, retrieval systems, and internal AI tools. - Work with image data, structured data, unstructured documents, embeddings, vector databases, and tool-calling workflows. - Translate ambiguous business and operational problems into practical AI/ML solutions. - Build data pipelines, inference services, evaluation workflows, and production-ready AI systems. - Evaluate model and agent performance, identify failure modes, and improve reliability over time. - Collaborate with product, engineering, venture, and stakeholder teams to validate concepts and ship working products. - Operate with autonomy in a fast-moving venture environment where priorities, requirements, and available data may evolve quickly. Qualifications - Strong Python engineering skills and experience building production-oriented AI/ML systems. - Hands-on experience with machine learning fundamentals, model evaluation, training workflows, and data processing pipelines. - Experience building or deploying computer vision systems such as image detection, classification, object recognition, or related workflows. - Experience working with modern LLMs, Generative AI tools, and AI-assisted development workflows. - Hands-on experience building agentic AI workflows, multi-step LLM systems, tool-calling systems, or AI automation workflows. - Experience building RAG, retrieval, or knowledge systems using embeddings, vector databases, document stores, structured data, or graph-based approaches. - Experience deploying AI/ML systems into production environments, including inference services, monitoring, evaluation, and deployment workflows. - Experience with cloud environments such as AWS, Azure, or GCP. - Strong ownership mindset with the ability to operate without fully defined requirements, proactively identify next steps, and communicate tradeoffs clearly. - Strong communication skills and ability to collaborate across technical and non-technical teams. Nice to Have - Experience with industrial, manufacturing, robotics, logistics, or operational data environments. - Familiarity with edge deployment, camera systems, IoT data, sensor data, or real-time inference workflows. - Experience with tools such as LangGraph, PydanticAI, LangChain, LlamaIndex, ChromaDB, Pinecone, Weaviate, FAISS, pgvector, Neo4j, or similar. - Experience working in startups, venture studios, or early-stage product environments. - Experience building AI-powered internal tools, developer workflows, or automation systems beyond core product work. Company Description UP.Labs builds high-growth technology startups that enable faster, cleaner, and safer movement of people and goods. We partner with leading corporations and entrepreneurs to identify major industry opportunities, validate new venture concepts, and launch software and hardware companies from the ground up. Our team works at the earliest stage of company creation, where ideas are still forming, requirements are evolving, and technical validation is critical. We take ventures from concept through MVP and help recruit the full-time team that will scale the business. This environment requires people who are comfortable operating with ambiguity, making pragmatic technical decisions, and helping turn early product concepts into real, working systems. Location: Remote

• Develop and maintain core School of Splunk Field Sales Enablement portfolio • Design and deliver AI-focused onboarding and upskilling curricula • Integrate critical technical sales skills into curriculum for learners to develop mastery • Compose test questions, evaluations, and assessments that validate proficiency • Develop and continuously refresh learning content that reflects the messaging and positioning related to Splunk platform • Work with key stakeholders to develop technical seller training programs • Serve as a trusted advisor to technical sales stakeholders and SMEs • Update and optimize existing GFE training assets to reflect Cisco's current strategic direction