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 description reflects the general nature of the role. It’s not a complete list of responsibilities—we believe in flexibility, initiative, and growing together. Knowledge, Skills & Experience Advanced Degree: Master’s in Computer Science, AI, or related field with focus on LLMs, NLP, or Reinforcement Learning. LLM & Agentic Expertise: Hands-on experience fine-tuning open-source or proprietary LLMs (Hugging Face, OpenAI API, etc.). Familiarity with agent frameworks (LangChain, LlamaIndex, or custom pipelines). Software Engineering Skills: Solid Python (preferred) or C# coding, REST/gRPC API design and deployment in cloud environments. Security & Ethics Awareness: Understanding of LLM governance, bias mitigation, and data privacy best practices. Collaboration & Curiosity: Eager to learn from both ML researchers and reservoir experts—strong communicator and team player. Why Join Us? Competitive Package Innovation at Scale: Ownership of end-to-end LLM pipelines that redefine how engineers work. High Impact: Your work will directly accelerate CMG’s simulation products and shape industry-leading digital-twin and optimization technologies. CMG’s total rewards program includes: A competitive salary A performance-based bonus program Learning and development opportunities Retirement contributions Generous medical and dental benefits 20 days of vacation per year plus flex days No need to call us about the status of your application. We promise—we’re reviewing every submission, and if your skills are a match, you’ll hear from us! We kindly request that external recruiters and agencies refrain from submitting unsolicited resumes or candidate profiles. Submissions without a signed agreement in place will not be considered and will become the property of CMG. About Us Innovators in Simulation Technology CMG (TSX:CMG) is a global software and consulting company that combines science and technology with deep industry expertise to solve complex subsurface and surface challenges for the new energy industry around the world. CMG is headquartered in Calgary, AB, with offices in Houston, London, Dubai, Bogota, Rio de Janeiro, Bengaluru, and Kuala Lumpur. For more information, please visit https://www.cmgl.ca #J-18808-Ljbffr