This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google and top customers.

You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest-generation models.

We are looking for engineers with a strong track record of building and shipping AI-powered software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production.

The ideal candidate will be motivated by the opportunity to drive product & business impact.

Key responsibilities:

• Harness frontier models to drive real-world high-impact outcomes

• Build evaluations, training data, and infrastructure to support AI deployments and rapid iterations

• Collaborate with researchers and product managers to translate research advancements into tangible product features.

• Contribute to the development of best practices for building and deploying generative AI applications.

• Contribute signal to influence the development of frontier models

• Lead the architecture and development of new products & features from 0 to 1.

About you:

In order to set you up for success as a Staff Research Engineer, Applied AI at Google DeepMind, we look for the following skills and experience:

Required Skills:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development, and with data structures/algorithms.

• 5 years of hands-on experience in AI research (e.g. RL, finetuning, evals), AI applications, or model deployment

• Proven experience in rapidly developing and shipping software products.

• Deep understanding of software development best practices, including testing & deployment.

• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).

• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

• Ability to work in a fast-paced environment and adapt to changing priorities.

Preferred Skills:

• Experience with generative AI research or applications.

• Contributions to open-source projects.

• Experience working in, or founding early stage startups.

• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineer with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits.

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The ideal candidate will have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users. They will also have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code or container orchestration.

Responsibilities:

• Design and build infrastructure that serves Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models

• Collaborate with CSP partner engineering teams to resolve operational issues, influence provider roadmaps, and stand up end-to-end serving on new cloud platforms

• Design and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions

• Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity

• Contribute to capacity planning and autoscaling strategies that dynamically match supply with demand across CSP validation and production workloads

• Optimise inference cost and performance across providers,designing workload placement and routing systems that direct requests to the most cost-effective accelerator and region

• Contribute to inference features that must work consistently across all platforms

• Analyse observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

Requirements:

• Significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users

• Experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code or container orchestration

• Strong interest in inference

• Thrive in cross-functional collaboration with both internal teams and external partners

• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems

• Are highly autonomous and self-driven, taking ownership of problems end-to-end with a bias toward flexibility and high-impact work

• Pick up slack, even when it goes outside your job description

Preferred skills:

• Direct experience working with CSP partner teams to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings

• A background in building platform-agnostic tooling or abstraction layers that work across cloud providers

• Hands-on experience with capacity management, cost optimisation, or resource planning at scale across heterogeneous environments

• Strong familiarity with LLM inference optimisation, batching, caching, and serving strategies

• Experience with Machine learning infrastructure including GPUs, TPUs, Trainium, or other AI accelerators

• Background designing and building CI/CD systems that automate deployment and validation across cloud environments

• Solid understanding of multi-region deployments, geographic routing, and global traffic management

• Proficiency in Python or Rust

Salary Range: $300,000-$485,000 USD

Experience Level: Staff

Employment Type: Full-time

Workplace Type: Hybrid

Category: Engineering

Industry: Technology

Required Skills:

• High-performance, large-scale distributed systems

• Cloud computing (AWS, GCP, Azure)

• Kubernetes

• Infrastructure as Code

• Container orchestration

• Inference

• Cross-functional collaboration

• Autonomy and self-driven

• Platform-agnostic tooling

• Capacity management

• Cost optimisation

• Resource planning

• LLM inference optimisation

• Machine learning infrastructure

• CI/CD systems

• Multi-region deployments

• Geographic routing

• Global traffic management

• Python

• Rust

Preferred Skills:

• Direct experience working with CSP partner teams

• Building platform-agnostic tooling

• Hands-on experience with capacity management

• Strong familiarity with LLM inference optimisation

• Experience with Machine learning infrastructure

• Background designing and building CI/CD systems

• Solid understanding of multi-region deployments

• Proficiency in Python or Rust

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This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google and top customers.

You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest-generation models.

We are looking for engineers with a strong track record of building and shipping AI-powered software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production.

The ideal candidate will be motivated by the opportunity to drive product & business impact.

Key responsibilities:

• Harness frontier models to drive real-world high-impact outcomes

• Build evaluations, training data, and infrastructure to support AI deployments and rapid iterations

• Collaborate with researchers and product managers to translate research advancements into tangible product features.

• Contribute to the development of best practices for building and deploying generative AI applications.

• Contribute signal to influence the development of frontier models

• Lead the architecture and development of new products & features from 0 to 1.

About you:

In order to set you up for success as a Staff Research Engineer, Applied AI at Google DeepMind, we look for the following skills and experience:

Required Skills:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development, and with data structures/algorithms.

• 5 years of hands-on experience in AI research (e.g. RL, finetuning, evals), AI applications, or model deployment

• Proven experience in rapidly developing and shipping software products.

• Deep understanding of software development best practices, including testing & deployment.

• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).

• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

• Ability to work in a fast-paced environment and adapt to changing priorities.

Preferred Skills:

• Experience with generative AI research or applications.

• Contributions to open-source projects.

• Experience working in, or founding early stage startups.

• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineer with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits.

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Microsoft AI are looking for a talented Member of Technical Staff, Evaluations Engineer to help build the next wave of capabilities of our personalized AI assistant, Copilot. We're looking for someone who will bring an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective.

About the Role

We're looking for someone who will contribute to the development of AI models that are powering our innovative products. You will actively contribute to the development of AI models that are powering our innovative products. You will wear multiple hats and work on engineering, research, and everything in between. Your contributions will span model architecture, data curation, training and inference infrastructures, evaluation protocols, alignment and reinforcement learning from human feedback (RLHF), and many other exciting topics at the cutting edge of AI.

Accountabilities

• Develop and tune the pretraining scalable software for Nvidia GB200 72NVL CX8 and AMD MIxxx architectures.
• Benchmark GB200 and AMD MIxxx GPU clusters.
• Gather data and insights to develop the pretraining compute roadmap.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Technical skills:

• Experience with generative AI.
• Experience with distributed computing.

Personal attributes:

• Enjoy working in a fast-paced, design-driven, product development cycle.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.

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