Lead and conduct experimental physics research and development of advanced optical microscopy systems for semiconductor inspection.
Responsibilities
Develop advanced optical and electro‑optical modules combining lasers, light sources, detectors, high‑end optics, and electrical systems
Design, build, execute, and analyze laboratory experiments to validate optical system concepts and performance
Perform physics‑based simulations, optical system modeling, data analysis, and performance budgeting
Lead investigations of complex physical problems, identify root causes, and define practical technical solutions
Collaborate with multidisciplinary R&D teams, including applications, algorithms, electronics, mechanics, software, system engineering, and external suppliers
Requirements
PhD in Experimental Physics, Electro‑Optics, Applied Physics, or a related field
Nice to have: experience in semiconductor industry
Nice to have: experience in optical inspection systems
Lead and develop a global Solutions Consulting team, integrating Forward Deployed Engineers and expanding technical capabilities to support enterprise AI and workflow automation.
Responsibilities
Lead, coach and develop the global Solutions Consulting team
Recruit and integrate Forward Deployed Engineers
Assess capability gaps and implement development plans
Prioritise team resources across regions
Build a culture of accountability, experimentation, collaboration and knowledge sharing
Lead incident response and build data pipelines to improve reliability for NVIDIA AI cloud services.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Serve as incident commander for high‑severity incidents
Build and maintain data pipelines for reliability reporting
Manage end-to-end data processes for AI model training and evaluation, from data definition and creation to assessing and validating model outputs.
Responsibilities
Manage end-to-end data processes for AI model training and evaluation, from data definition and creation to assessing and validating model outputs
Work with generative AI models using prompt engineering to support automated model evaluation and synthetic data generation
Develop and adapt evaluation methodologies, with a particular focus on automated and scalable approaches
Work closely with data scientists, product managers, and data engineers to define data requirements, identify gaps, build data pipelines, and proactively solve data challenges to produce high-quality datasets
Evaluate model training data and results, conduct in-depth analyses (including error analysis), and define and monitor metrics/KPIs to assess model performance
Liaise with clients to collect data in line with project requirements
Conduct benefits benchmarking, claims analysis, feasibility assessments and cost-benefit analysis to support plan design decisions
Support Health Consultants and Senior Consultants with new business opportunities and sales channel partners
Use Mercer Health tools and products effectively to complete project tasks
Collaborate with colleagues across Marsh McLennan businesses and Mercer teams to develop intellectual capital for webinars, forums, publications and points of view
As a Senior Software Engineer on the GAIL Core Team, you will own the hardest engagements, set the quality standard for the entire practice, and build the infrastructure that scales it. This is hands-on, customer-facing work, not theoretical process, and its impact compounds with every engagement you lead and every engineer you bring up behind you.
Responsibilities
Lead the most complex GAIL and Go-Live Support engagements, including large-scale enterprise deployments, escalations, and high-stakes go-lives where depth and experience matter most.
Own and evolve the GAIL playbook, keeping deployment standards, required gates, and prescribed sequences current, accurate, and actionable across the program.
Drive quality standards across the GAIL practice by defining what great looks like and holding the line on it.
Build, maintain, and push shared GAIL tooling across all engagements, reducing reinvention and raising the floor for every engineer in the rotation.
Mentor and ramp incoming GAIL engineers through structured onboarding, shadowing, and coaching on first customer interactions.
Senior Associate, Applied AI/ML Engineer designing, building, and productionizing Generative AI and Agentic AI solutions.
Responsibilities
Design, develop, and deploy GenAI and Agentic AI solutions that improve automation, decision‑making, and user experience across business workflows.
Build LLM/SLM‑powered applications including RAG‑based systems, summarization/extraction pipelines, chat/coplay experiences, and tool‑using agents.
Engineer production‑grade services using Java and/or Python (REST/gRPC APIs, microservices, libraries), following secure coding and reliability best practices.
Develop prompt strategies and prompt engineering assets (templates, routing, guardrails), and implement automated evaluation to improve quality over time.
Build and maintain data pipelines and processing workflows required for ML/GenAI use cases using cloud services.
Requirements
Undergraduate degree in Computer Science, Data Science, Machine Learning, or related field
Master’s degree in Computer Science, Data Science, Machine Learning, or related field
Design and deliver customer‑facing AI proof of concepts on SAP BTP, build and deploy machine learning models, architect agentic AI solutions, and contribute to SAP’s best practices for AI on BTP.
Responsibilities
Design and deliver customer‑facing AI proof of concepts on SAP BTP
Develop and deploy machine learning models on SAP BTP
Design agentic AI architectures using LangGraph, LangChain, and BTP AI services
Build front‑end applications in JavaScript, HTML, and SAP Fiori web components
Apply data science techniques and statistical analysis to build predictive models
Requirements
A degree in Computer Science, Engineering, or a related field
Support SAP's demand generation efforts, working with Digital Campaign Managers to deliver the data, insights, and automation that help sales teams reach the right accounts.
Responsibilities
Profile and segment target accounts, building and maintaining high-quality account lists using data and market insights
Develop and maintain Power BI dashboards and reports that deliver actionable insights for sales and marketing decisions
Improve data quality, consistency, and accessibility across reporting tools and business processes
Build automation solutions using Power Automate, Python, or similar tools to reduce repetitive tasks and increase efficiency
Explore AI-powered tools and emerging technologies to improve team productivity, and contribute to innovation projects
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