Your responsibilities will include building and extending components of the core Databricks infrastructure, architecting multi-cloud systems and abstractions to allow the Databricks product to run on top of existing Cloud providers, improving software development workflows for engineering and operational efficiency, using our own data and AI platform to analyze build and test logs and metrics to identify areas for improvement, developing automated build, test, and release infrastructures, and setting and upholding the standard for engineering processes to support high-quality engineering.

To succeed in this role, you will need a BS (or higher) in Computer Science, or a related field, and 5+ years of experience writing production code in one of Java, Scala, Go, C++, or Python. You should also have passion for building highly scalable and reliable infrastructure, experience architecting, developing, and deploying large-scale distributed systems at scale, and experience with cloud APIs and cloud technologies such as AWS, Azure, GCP, Docker, Kubernetes, or Terraform.

In addition to a competitive salary, we offer comprehensive health coverage, 401(k) plan, equity awards, flexible time off, paid parental leave, family planning, gym reimbursement, annual personal development fund, work headphones reimbursement, employee assistance program, and business travel accident insurance.

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This involves writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform).

You will be part of a team that builds highly technical products that fulfil real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.

Our engineering teams build one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day.

We run thousands of Kubernetes clusters across all regions and orchestrate millions of VMs on a daily basis.

Competencies:

• BS/MS/PhD in Computer Science, or a related field
• 10+ years of production level experience in one of: Java, Scala, C++, or similar language
• Comfortable working towards a multi-year vision with incremental deliverables
• Experience in architecting, developing, deploying, and operating large scale distributed systems
• Experience working on a SaaS platform or with Service-Oriented Architectures
• Good knowledge of SQL
• Experience with software security and systems that handle sensitive data
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes

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As a software engineer with a backend focus, you will work closely with your team and product management to prioritise, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform).

Some example teams you can join include:

Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Compute Fabric: Build the resource management infrastructure powering all the big data and machine learning workloads on the Databricks platform in a robust, flexible, secure, and cloud-agnostic way. Data Plane Storage: Deliver reliable and high-performance services and client libraries for storing and accessing humongous amounts of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Enterprise Platform: Offer a simple and powerful experience for onboarding and managing all of their data teams across 10ks of users on the Databricks platform. Observability: Provide a world-class platform for Databricks engineers to comprehensively observe and introspect their applications and services. Service Platform: Build high-quality services and manage the services in all environments in a unified way. Core Infra: Build the core infrastructure that powers Databricks, making it available across all geographic regions and Cloud providers.

The ideal candidate will have:

• BS/MS/PhD in Computer Science, or a related field
• 10+ years of production-level experience in one of: Java, Scala, C++, or similar language
• Comfortable working towards a multi-year vision with incremental deliverables
• Experience in architecting, developing, deploying, and operating large-scale distributed systems
• Experience working on a SaaS platform or with Service-Oriented Architectures
• Good knowledge of SQL
• Experience with software security and systems that handle sensitive data
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes

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This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform).

You will be part of one of the following teams:

Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Compute Fabric: Build the resource management infrastructure powering all the big data and machine learning workloads on the Databricks platform in a robust, flexible, secure, and cloud-agnostic way. Data Plane Storage: Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Enterprise Platform: Offer a simple and powerful experience for onboarding and managing all of their data teams across 10ks of users on the Databricks platform. Observability: Provide a world class platform for Databricks engineers to comprehensively observe and introspect their applications and services. Service Platform: Build high-quality services and manage the services in all environments in a unified way. Core Infra: Build the core infrastructure that powers Databricks, making it available across all geographic regions and Cloud providers.

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As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform).

Some example teams you can join:

Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Compute Fabric: Build the resource management infrastructure powering all the big data and machine learning workloads on the Databricks platform in a robust, flexible, secure, and cloud-agnostic way. Data Plane Storage: Deliver reliable and high-performance services and client libraries for storing and accessing humongous amounts of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Enterprise Platform: Offer a simple and powerful experience for onboarding and managing all of their data teams across 10ks of users on the Databricks platform. Observability: Provide a world-class platform for Databricks engineers to comprehensively observe and introspect their applications and services. Service Platform: Build high-quality services and manage the services in all environments in a unified way. Core Infra: Build the core infrastructure that powers Databricks, making it available across all geographic regions and Cloud providers.

Competencies:

BS/MS/PhD in Computer Science, or a related field 10+ years of production-level experience in one of: Java, Scala, C++, or similar language Comfortable working towards a multi-year vision with incremental deliverables Experience in architecting, developing, deploying, and operating large-scale distributed systems Experience working on a SaaS platform or with Service-Oriented Architectures Good knowledge of SQL Experience with software security and systems that handle sensitive data Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes.

Pay Range Transparency: The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

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Microsoft are looking for a talented Member of Technical Staff - Machine Learning (AI Team) at their Redmond office. 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 - Machine Learning (AI Team), you will work to create LLM models for general purpose capabilities and for products. You may be responsible for developing new methods to train core LLM capabilities (including agentive), collecting data, evaluating LLMs, creating data flywheels, tooling for LLM training/evals, writing production quality code, and creating new user-facing features. You should be comfortable creating Reinforcement Learning data, fine tuning, or training classifiers or engineering prompts to support Microsoft products and the Cloud API.

Accountabilities

• Leverage subject matter expertise to improve model quality for interactive and agentive experiences.
• Oversee data acquisition or generation efforts, ensuring that the data meets the model needs.
• Generalize machine learning (ML) solutions into repeatable frameworks.
• Lead evaluation efforts of models, including those deployed within Microsoft products and the Cloud API.
• Track advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Computer Science or related technical field AND 4+ 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 prompting, evaluating, and working with large language models.
• Experience writing production-quality Python code.

Personal attributes:

• Demonstrated engineering experience or research experience (e.g. creating or leading the creation of a feature in a different company, complex graduate work, research papers, or other experience).

Benefits

• Software Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year.
• Certain roles may be eligible for benefits and other compensation.

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