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Member of Technical Staff, Software Engineer - MAI SuperIntelligence team

Microsoft

Member of Technical Staff, Software Engineer - MAI SuperIntelligence team

Microsoft

Switzerland, Zürich, Zürich

·

On-site

·

Full-time

·

1mo ago

Overview Help build the infrastructure that powers training, evaluation, and data platforms for reliable deployment of world-class foundational AI models. We are on a mission to create state-of-the-art AI models and deploy them across Microsoft products at an unprecedented scale.

You’ll collaborate across engineering and research to design, evolve, and operate core research infrastructure, so that product teams can train faster, evaluate more rigorously, and ship with confidence. You’ll work closely with the teams that transform pre-trained models into the consumer Copilot experience.

Microsoft’s mission is to empower every person and every organization to achieve more, and we build on values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive. Microsoft Superintelligence Team This role is part of Microsoft AI's Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!

  • Responsibilities- 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.
  • 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, Open Telemetry).
  • Architect and operate services on Azure cloud platforms, managing infrastructure-as-code (Terraform/Helm), secrets, networking, and storage.
  • 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.
  • Enforce security and compliance policies for data access, container hardening, and supply-chain integrity, and partner with security and privacy teams to maintain robust practices in multi-tenant environments and secret management.
  • Collaborate cross-functionally with data, model, and product teams to align infrastructure roadmaps with training needs, evaluation protocols, and Copilot product goals.

Qualifications:

Required skills

  • Strong software engineering background building reliable, scalable production systems (Python preferred)
  • 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)
  • Platform reliability and operability: observability, metrics, logging, tracing, alerting (Prometheus, Grafana, Open Telemetry)

Desired skills

  • Building secure, reproducible platforms using CI/CD, infrastructure‑as‑code (Terraform, Helm), container security, and secrets management
  • Experience working closely with AI researchers in fast‑moving, experimental, frontier‑scale research environments and building internal tools (CLIs, portals, APIs) to boost productivity

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

Microsoft

A software corporation that develops, manufactures, licenses, supports, and sells a range of software products and services.

10,001+

Employees

Redmond

Headquarters

$3000B

Valuation

Reviews

3.8

5 reviews

Work Life Balance

4.1

Compensation

4.3

Culture

3.4

Career

3.2

Management

3.0

65%

Recommend to a Friend

Pros

Excellent compensation and benefits package

Four-day workweek with improved work-life balance

Supportive managers and teams

Cons

High-pressure environment causing anxiety

Unprofessional interview processes

Limited creative work opportunities

Salary Ranges

5,571 data points

Junior/L3

Mid/L4

Junior/L3 · Advertising Client Success

2 reports

$163,358

total / year

Base

$141,875

Stock

-

Bonus

-

$163,358

$163,358

Interview Experience

7 interviews

Difficulty

3.7

/ 5

Duration

14-28 weeks

Offer Rate

14%

Experience

Positive 14%

Neutral 29%

Negative 57%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Technical Interview

5

Onsite/Virtual Interviews

6

Final Round

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience