People are our most valuable asset. join cmg’s innovation lab as machine learning engineer specializing in agentic system design and large-language models (llms) to streamline subsurface workflows. you’ll fine-tune, orchestrate, and deploy llm-powered agents that can automate data preparation, report generation, and decision-support tasks for reservoir engineers. key responsibilities llm fine-tuning & prompt engineering: adapt state-of-the-art llms (e.g., gpt-style, llama-based) to domain-specific tasks—data extraction from well logs, automated reporting, anomaly detection. create, iterate, and optimize prompts and training pipelines for few-shot and reinforcement-based fine-tuning. agentic workflow design: build multi-step “agents” that chain llm calls, external apis, and rule-based checks to fully automate routine subsurface tasks. ensure agents handle error recovery, context management, and scalability under production loads. backend & orchestration: develop microservices in python or c# to serve llm agents via api, integrating with cmg’s data stores and simulation tools. containerize and deploy these services, instrumenting them with monitoring, logging, and performance metrics. scalability & governance: collaborate with devops to scale inference horizontally, balancing cost, latency, and throughput. cross-functional delivery: partner with ux designers to provide intuitive interfaces (chatbots, dashboards) for engineers to interact with agents. lead agile sprints, demos, and retrospectives—communicating progress and trade-offs to product and domain teams. note: this des...
18 hours ago be among the first 25 applicants direct message the job poster from computer modelling group join cmg’s innovation lab as machine learning engineer with a master’s or phd focused on physics-informed neural networks (pinns), fourier neural operators (fnos), deep reinforcement learning (drl) for reservoir and cfd applications. in this role you’ll blend advanced ml theory with practical reservoir modeling, driving accuracy and performance improvements from concept through production. key responsibilities simulation & ml integration: - design and implement pinn-based solvers, fno surrogates or others to accelerate reservoir simulation and optimize subsurface workflows. - integrate your models into cmg’s simulation pipeline, ensuring numerical stability and scientific rigor. - build scalable data pipelines for large-scale geological and production datasets. - containerize and deploy inference services, wrapping pinn/fno models with robust apis. strategic roadmap: - collaborate with domain experts to define a multi-year ml/ai strategy for reservoir simulation. - identify key research areas and drive prototyping of next-generation ml solvers. early-stage research & delivery: - lead r&d; projects—from literature review and algorithm design through hands-on implementation and performance benchmarking. - validate model accuracy against high-fidelity simulators and real field data cross-functional collaboration: - pair with software engineers to productionize algorithms under clean-architecture and ci/cd best practices. - present findings, trade-offs, and perfo...
Pioneering trusted medical solutions to improve the lives we touch: convatec is a global medical products and technologies company, focused on solutions for the management of chronic conditions, with leading positions in advanced wound care, ostomy care, continence care, and infusion care. with around 10,000 colleagues, we provide our products and services in almost 100 countries, united by a promise to be forever caring. our solutions provide a range of benefits, from infection prevention and protection of at-risk skin to improved patient outcomes and reduced care costs. convatec’s revenues in 2023 were over $2 billion. the company is a constituent of the ftse 100 index (lse:ctec). to learn more about convatec, please visit are you a seasoned data & bi engineer looking for a role where you can truly make an impact? do you thrive on transforming complex data into actionable insights and building robust data platforms? we're on a transformative journey to modernize our global data platform, and we're seeking a proactive and technically skilled professional with 5-7 years of experience to join our team. this is a unique opportunity to contribute hands-on across the entire data engineering, modeling, and reporting lifecycle. you'll start with foundational work like migrating from legacy systems to snowflake , and progressively deepen your skills as you help us build advanced architectures in microsoft fabric, data mesh, and sap analytics cloud . if you're eager to learn, grow, and shape the future of our data landscape, we want to hear from you! main responsibilities: suppor...
18 hours ago be among the first 25 applicantsdirect message the job poster from computer modelling groupjoin cmg's innovation lab as machine learning engineer with a master's or phd focused on physics-informed neural networks (pinns), fourier neural operators (fnos), deep reinforcement learning (drl) for reservoir and cfd applications. in this role you'll blend advanced ml theory with practical reservoir modeling, driving accuracy and performance improvements from concept through production.key responsibilitiessimulation & ml integration:design and implement pinn-based solvers, fno surrogates or others to accelerate reservoir simulation and optimize subsurface workflows.integrate your models into cmg's simulation pipeline, ensuring numerical stability and scientific rigor.build scalable data pipelines for large-scale geological and production datasets.containerize and deploy inference services, wrapping pinn/fno models with robust apis.strategic roadmap:collaborate with domain experts to define a multi-year ml/ai strategy for reservoir simulation.identify key research areas and drive prototyping of next-generation ml solvers.early-stage research & delivery:lead r&d; projects—from literature review and algorithm design through hands-on implementation and performance benchmarking.validate model accuracy against high-fidelity simulators and real field datacross-functional collaboration:pair with software engineers to productionize algorithms under clean-architecture and ci/cd best practices.present findings, trade-offs, and performance metrics to stakeholders in product and s...
18 hours ago be among the first 25 applicants direct message the job poster from computer modelling group join cmg’s innovation lab as machine learning engineer with a master’s or phd focused on physics-informed neural networks (pinns), fourier neural operators (fnos), deep reinforcement learning (drl) for reservoir and cfd applications. in this role you’ll blend advanced ml theory with practical reservoir modeling, driving accuracy and performance improvements from concept through production. key responsibilities simulation & ml integration: design and implement pinn-based solvers, fno surrogates or others to accelerate reservoir simulation and optimize subsurface workflows. integrate your models into cmg’s simulation pipeline, ensuring numerical stability and scientific rigor. build scalable data pipelines for large-scale geological and production datasets. containerize and deploy inference services, wrapping pinn/fno models with robust apis. strategic roadmap: collaborate with domain experts to define a multi-year ml/ai strategy for reservoir simulation. identify key research areas and drive prototyping of next-generation ml solvers. early-stage research & delivery: lead r&d projects—from literature review and algorithm design through hands-on implementation and performance benchmarking. validate model accuracy against high-fidelity simulators and real field data cross-functional collaboration: pair with software engineers to productionize algorithms under clean-architecture and ci/cd best practices. present findings, trade-offs, and performance metrics to stakeholders i...
At kpler, we are dedicated to helping our clients navigate complex markets with ease. by simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors. since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms.our team of over 600 experts from 35+ countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success. we are seeking a motivated and detail-oriented operations research (or) engineer to join our team. in this role, you will contribute to the design, modelling, and implementation of optimisation, simulation, and analytics solutions to drive better business decisions. you will work closely with cross-functional teams to solve complex problems and drive operational efficiency responsibilities: develop and implement mathematical models (optimisation, simulation, statistical) to support business processes and decision-making. assist in the development of algorithms for logistics, scheduling, inventory management and resource allocation problems. use software tools like python, sql, or-tools, and similar to build and test models. analyse results, identify trends, and prepare detailed reports and visualisations for stakeholders. support the senior or engineers in research, model validation, and implementation p...
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