• Lead the planning, execution, and delivery of multiple AI initiatives, ensuring projects meet scope, timelines, quality expectations, and business objectives • Mentor and support AI Engineers by setting clear direction, providing coaching, and building a high-performing project team • Partner with stakeholders across product, science, clinical, operations, and engineering to define requirements, priorities, milestones, risks, and success metrics • Translate stakeholder needs into technical roadmaps, delivery plans, and resourcing strategies for AI-powered products and platforms • Guide solution design, software development, model integration, testing, deployment, and operational support across the AI project portfolio • Drive strong AI research and engineering practices across the team • Coordinate dependencies, remove blockers, and communicate project status, risks, and tradeoffs clearly to leadership and stakeholders • Balance innovation and experimentation with execution discipline, scalability, reliability, and compliance considerations • Contribute to hiring, onboarding, team planning, and continuous improvement of delivery processes and engineering standards

Role Description - Develop end-to-end machine learning solutions for challenging prediction and modeling problems. - Analyze datasets and define appropriate modeling approaches, validation strategies, and evaluation metrics. - Perform exploratory data analysis, feature engineering, and data preprocessing. - Train, tune, and evaluate machine learning models across tabular, text, image, and time-series datasets. - Review and validate the technical quality of machine learning projects and deliverables. - Identify opportunities to improve model performance through systematic experimentation and iteration. Qualifications - Must-Have: - Master's degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field from a top-tier university. - 2+ years of professional experience in machine learning, applied AI, data science, or a closely related field. - Strong proficiency in Python and modern machine learning frameworks (e.g., scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow). - Demonstrated experience building end-to-end machine learning solutions, including data preparation, model development, validation, and evaluation. - Strong understanding of model evaluation metrics, validation methodologies, and experimental design. - Experience with one or more of the following areas: tabular machine learning, natural language processing, computer vision, recommendation systems, ranking systems, time-series forecasting. - Ability to work independently on open-ended machine learning problems and deliver high-quality technical outputs. - Preferred: - PhD from a leading research university. - Experience at leading technology companies, AI labs, research institutions, or high-growth startups. - Participation in competitive machine learning or data science competitions. - Experience optimizing models against performance-based evaluation metrics. - Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning. - Publications, patents, or significant open-source contributions in machine learning or AI. - Experience reviewing, mentoring, or evaluating the work of other machine learning practitioners. Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com - PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Role Description We’re focused on helping people with diabetes manage their health with life-changing products that provide accurate data to drive better-informed decisions. We’re revolutionizing the way people monitor their glucose levels with our new sensing technology. This Senior AI Engineer position can work remotely within the U.S. Senior AI SW Engineer to work on a Go-based medical device web application and a modern Software as a Service (SaaS) cloud platform aimed at enhancing user health. This role will help improve existing platforms, design and implement cloud-based services, build internal tooling, and bring practical AI capabilities into safe, reliable health-focused products. What You’ll Do - Enhance and maintain our Go-based healthcare platforms, focusing on reliability, performance, security, scalability, and user experience. - Design, build, test, and deploy cloud-native SaaS services, APIs, and data workflows using Go and modern engineering practices. - Develop high-volume, low-latency distributed systems supporting a global healthcare platform. - Design and integrate AI capabilities, including model integrations, inference services, and evaluation workflows to drive advanced features and health insights. - Collaborate with internal and external partners to build secure APIs that enable compliant sharing and use of medical data. - Partner cross-functionally with product, quality, regulatory, security, DevOps, and engineering teams to deliver safe, scalable, and compliant medical device software. - Work with InfoSec to design and implement secure, standards-aligned solutions. - Write clean, testable, and maintainable code with strong test coverage. - Ensure performance, availability, and scalability through high-quality engineering and design practices. - Contribute to architecture and technical strategy, translating architectural goals into clear service boundaries, reusable patterns, and maintainable implementations. - Drive system improvements to align platforms with evolving architectural standards. - Build internal tools, automation, dashboards, and developer utilities to improve engineering productivity, operational visibility, and release confidence. - Document system design using diagrams, flowcharts, and technical specifications. - Participate actively in agile development, contributing to planning, development, testing, and delivery. - Lead technical discussions, design reviews, and code reviews to uphold engineering excellence. - Stay current with AI, cloud, healthcare, and software engineering trends, applying relevant innovations. - Demonstrate ownership, strong technical judgment, collaboration, and a commitment to continuous learning. Qualifications - Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field. - 8+ years of relevant experience, or a Master’s degree with 6+ years of experience. - Hands-on experience with applied AI/ML concepts, including model integration, inference workflows, evaluation, feature engineering, prompt/model orchestration, or intelligent automation. - Strong backend engineering experience in Go, including APIs, concurrency, testing, and maintainable system design. - Experience designing and contributing to scalable, highly available, and observable system architectures. - Experience building and maintaining distributed systems, including asynchronous processing, messaging, and backend data workflows. - Strong experience developing and integrating RESTful APIs and microservices. - Familiarity with database technologies (e.g., SQL Server, PostgreSQL, or similar relational/NoSQL systems). - Experience with cloud platforms and modern development practices, including CI/CD, containers, infrastructure automation, observability, and version control. - Solid computer science fundamentals and problem-solving skills. - Experience working in agile development environments. - Practical working knowledge of Linux systems. - Strong communication skills (written and verbal) and ability to collaborate across teams. - Demonstrated ownership, curiosity, and willingness to contribute beyond defined responsibilities. Preferred Qualifications - Experience with medical device software, digital health, wellness platforms, clinical applications, or regulated software development. - Familiarity with quality system practices, validation support, requirements traceability, risk-aware development, audit trails, and design documentation. - Experience with Kubernetes, Docker, Terraform, message queues, event-driven architectures, service observability, or platform engineering practices. - Exposure to MLOps, model versioning, monitoring, evaluation frameworks, retrieval-augmented generation, vector databases, or responsible AI practices. - Understanding of secure software development, privacy, access control, auditability, encryption, and responsible handling of health-related or sensitive user data. - Ability to mentor teammates through code reviews, documentation, knowledge sharing, and constructive technical feedback. Benefits - Career development with an international company where you can grow the career you dream of. - Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. - An excellent retirement savings plan with high employer contribution. - Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. - A company recognized as a great place to work in dozens of countries around the world and named one of the most admired companies in the world by Fortune. - A company that is recognized as one of the best big companies to work for as well as a best place to work for diversity, working mothers, female executives, and scientists.

• Architect and develop enterprise-scale multi-agent systems leveraging LLMs and autonomous agent frameworks using Google ADK, Agentspace, MCP, RAG, and A2A orchestration • Design and implement RAG pipelines using BigQuery and Vertex AI Engine for knowledge grounding and factually accurate responses • Optimize agents for orchestration, knowledge grounding, multi-step reasoning, and decision-making • Design and implement distributed training workflows, online inference systems, and low latency serving architectures optimized for real-world performance, using Google cloud-native services • Engineer scalable, secure, compliant and production-grade AI fabric and AI agent workflows using Vertex AI and modern cloud-native technologies • Create reusable agent orchestration layers, observability hooks, and governance frameworks that accelerate Agentic AI adoption across TAG brands • Partner with cross-functional stakeholders in translating business requirements into technical specifications • Own the full AI development lifecycle – from data collection and implementation to deployment and monitoring • Implement intelligent observability and automation strategies to ensure AI system reliability and performance at scale