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The Sr. AI Engineer will design and implement advanced AI systems to enhance instrument intelligence and lab automation across Life Sciences and Diagnostics sectors. They will lead complex AI projects and collaborate with cross-functional teams to translate product concepts into scalable AI architectures.
You will own the day-to-day product roadmap for member-facing mobile and web experiences, translating complex genomic intelligence into clear, trustworthy consumer products. You will lead the end-to-end member journey, utilizing analytics and user feedback to drive activation, engagement, and long-term retention.
You will explore and prototype new bioinformatics capabilities by combining genetic data, scientific knowledge, and AI reasoning. You are responsible for defining scientific hypotheses and creating evidence packages to hand off validated prototypes for productionization.
Design, build, and deploy intelligent agent solutions using the Microsoft AI ecosystem and Power Platform. Collaborate with cross-functional teams to integrate enterprise systems and ensure continuous improvement of AI-driven business processes.
The Product Developer will design, develop, and maintain software while operationalizing AI-driven capabilities across shipbuilding solutions. They will collaborate with cross-functional teams to troubleshoot technical issues and implement best practices for software quality.
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The Senior Security Engineer will own the technical security posture of platform, infrastructure, and AI-driven systems. Responsibilities include hardening cloud environments, remediating vulnerabilities, and implementing security guardrails for AI workflows.
Build and deploy production-grade AI/ML solutions that transform complex farm data into actionable intelligence. Collaborate with cross-functional teams to integrate models into real-time applications and monitor their performance using cloud infrastructure.
The Sales Specialist will own and drive end-to-end sales cycles for Data and AI solutions, focusing on prospecting, solutioning, and closing deals. They will build and expand pipelines while partnering with cloud providers to deliver value-based outcomes for enterprise and mid-market clients.
Design, build, and deploy intelligent agent solutions using the Microsoft AI ecosystem and Power Platform. Collaborate with cross-functional teams to integrate enterprise systems and ensure continuous improvement of AI-driven business processes.
Design and build enterprise-grade AI governance features including LLM gateways and network firewalls for developer environments. Collaborate with cross-functional teams and partners to integrate these tools into existing developer workflows and open-source ecosystems.
The Senior Manager will bridge the gap between pre-sales strategy and project delivery by designing and architecting high-impact data and AI solutions. They will lead technical discovery, define project scopes, and collaborate with delivery teams to ensure solutions align with client business objectives.
The Senior Manager will lead technical architecture and discovery projects while bridging the gap between pre-sales strategy and project delivery. They are responsible for scoping, designing scalable data and AI solutions, and providing expert guidance to delivery teams.
The Manager will lead efforts to strengthen AI governance, workforce, and digital infrastructure within Ministries of Health to support sustainable AI adoption. They will also manage key stakeholder relationships and synthesize research to inform global AI for health strategies.
The role involves developing target-state architectures and defining enterprise platform strategies to deliver scalable cloud and AI solutions. You will collaborate with cross-functional teams to operationalize DevOps processes and provide subject matter expertise on infrastructure engineering.
The role involves providing technical leadership for cloud software deployment, automating infrastructure, and managing CI/CD pipelines. You will also collaborate with architecture teams to design scalable, secure cloud environments and troubleshoot operational issues.
The Principal Architect leads the technical delivery approach across multi-disciplinary engagements in data, AI, and governance. This role also drives practice maturation by establishing delivery standards, engineering practices, and advisory frameworks to ensure consistent and scalable project outcomes.
The Director will personally lead the growth, commercialization, and scaling of the AI services practice by developing strategic pipelines and winning new business. They will also cultivate high-level partnerships and define the company's AI growth agenda across federal and commercial markets.
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Lead research and analytics to guide AI diagnostics investments by assessing technical readiness and market intelligence. Develop strategies and analytical tools to support Ministries of Health in scaling AI-driven healthcare solutions.
The Associate Director will serve as the senior technical expert in AI and machine learning, advising projects and Ministries of Health on responsible deployment strategies. They will also provide quality assurance, mentor technical teams, and translate complex technical concepts for non-technical stakeholders.
The Associate Director will lead the strategy and launch of National Health Intelligence Centers, partnering with Ministries of Health to implement AI-driven solutions for health systems management. They will manage a team, oversee technical direction, and foster relationships with donors and government stakeholders to ensure sustainable impact.
The AI Applications Engineer will design, execute, and operationalize fine-tuning workflows for large language models using various learning approaches. They will collaborate with cross-functional teams to translate requirements into engineered solutions while maintaining high standards for code and design.
The AI Research Engineer will design and ship advanced machine learning systems that bridge cutting-edge research with production engineering. This role involves managing the full lifecycle of AI projects, from problem framing and experimentation to deployment and continuous improvement.
The AI Infrastructure Engineer will focus on maximizing throughput and minimizing latency for large neural network systems. They will collaborate with cross-functional teams to translate requirements into optimized, well-engineered solutions for production AI workloads.
The Medical Director will lead clinical AI model training, testing, and surveillance, focusing on utilization management and evidence-based clinical criteria. This role serves as the primary clinical authority for guideline interpretation and collaborates with data science and AI teams to modernize clinical programs.
You will build and maintain AI-powered healthcare infrastructure, working across the full stack to develop voice and AI agents for clinical workflows. You will partner with product and design teams to turn business problems into production-ready solutions while ensuring high standards for reliability and safety.
Advise clients on mergers and acquisitions, corporate governance, and commercial transactions while navigating the legal landscape of AI and emerging technologies. Collaborate with cross-functional teams to deliver integrated solutions and actively grow your own client practice.
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The GTM Engineer will own the end-to-end GTM systems, including HubSpot administration, data integrity, and the implementation of automated workflows. They will partner with the Applied AI team to integrate AI-first solutions into revenue operations and optimize system architecture.
The AI Solutions Architect is responsible for identifying, designing, and scaling AI-enabled solutions while ensuring they are secure, compliant, and aligned with enterprise standards. This role bridges the gap between business needs and technical implementation by facilitating ideation workshops and maintaining an enterprise AI use case roadmap.
Engage in live, natural video conversations in Russian with other participants to provide data for AI model training. Discuss everyday topics to help AI models learn natural speech patterns, tone, and cultural nuances.
Engage in live, natural video conversations in Russian with other participants to provide data for AI model training. Discuss everyday topics to help AI systems learn natural speech patterns, tone, and cultural nuances.
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