At Fuse Energy, we're on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system.

As the Head of Engineering (AI) at Fuse Energy, you will lead the development and integration of AI across our platform—from intelligent forecasting models and optimization algorithms to personalized customer experiences and internal automation.

Responsibilities

• Own the AI engineering roadmap and lead the development of AI-first features
• Productionize ML models, ensuring scalability, performance, and observability
• Design the infrastructure for deploying and maintaining ML systems in production (e.g., MLOps, CI/CD for ML, model versioning)
• Build systems that integrate AI into key parts of our stack, such as:
• Forecasting customer demand and renewable generation
• Dynamic pricing and energy trading algorithms
• Intelligent alerts and personalized customer features
• Work closely with product and engineering leadership to identify high-impact AI opportunities
• Build and lead a high-performing team of AI engineers

Requirements

• Strong software engineering background with 5+ years of experience, including at least 2 years leading AI/ML engineering teams
• Deep experience deploying ML models into production environments
• Proficiency in designing scalable data pipelines and real-time inference systems
• Understanding of modern ML tooling and frameworks (e.g., PyTorch, TensorFlow, MLflow, AWS SageMaker)
• Strong cross-functional collaboration skills, particularly with data science and product teams
• Clear communication and an ability to prioritize for both experimentation and reliability

Bonus

• Familiarity with optimization, time series modeling, or forecasting
• Experience with large language models (LLMs), RAG, or generative AI in production
• Background in MLOps or AI infrastructure at scale

Benefits

• Competitive salary and an equity sign-on bonus
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Paid annual leave
• Breakfast and dinner allowance for office-based employees

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Microsoft AI are looking for a talented Member of Technical Staff, Software Engineer to join their MAI SuperIntelligence team in Zürich, Switzerland. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Member of Technical Staff, Software Engineer, you will design and build core platform services for scalable training and evaluation, including cluster orchestration, job scheduling, data and compute pipelines, and artifact management. You will standardize containerized workflows by maintaining Docker images, CI/CD, and runtime configurations; advocate for best practices in security, reproducibility, and cost efficiency. You will implement end-to-end observability and operations through metrics, tracing, logging, dashboard development, monitoring, and automated alerts for model training and platform health (using Prometheus, Grafana, OpenTelemetry). You will architect and operate services on Azure cloud platforms, managing infrastructure-as-code (Terraform/Helm), secrets, networking, and storage. You will enhance developer experience by creating tools, CLIs, and portals that simplify job submission, metrics analysis, and experiment management for generalist software engineering and research teams.

Accountabilities

• Design and build core platform services for scalable training and evaluation, including cluster orchestration, job scheduling, data and compute pipelines, and artifact management.
• Standardize containerized workflows by maintaining Docker images, CI/CD, and runtime configurations; advocate for best practices in security, reproducibility, and cost efficiency.

The Candidate we're looking for

Experience:

• Strong software engineering background building reliable, scalable production systems (Python preferred).

Technical skills:

• Hands-on experience supporting large-scale ML / LLM training, evaluation, or experimentation infrastructure.
• Operating GPU-heavy workloads in cloud environments using Docker and Kubernetes (scheduling, utilization, isolation).
• Designing and running data / compute pipelines and orchestration (e.g., Airflow, Argo) with object storage (Azure Blob / S3).

Personal attributes:

• Building secure, reproducible platforms using CI/CD, infrastructure-as-code (Terraform, Helm), container security, and secrets management.

Benefits

• Competitive salary and benefits package.
• Opportunity to work with a talented team of engineers and researchers.
• Access to cutting-edge technology and resources.
• Flexible work arrangements, including remote work options.

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