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About the Role

We are seeking a Cyber Security with strong expertise in implementing secure and compliant AI/ML solutions. The role will focus on ensuring responsible AI adoption, data security, compliance, and governance across AI/ML projects. The ideal candidate will have hands-on experience in security architecture, cloud platforms (especially Microsoft Azure), and governance frameworks, with proven knowledge of AI/ML lifecycle risks.

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Key Responsibilities

• AI/ML Security & Governance

  • Design, implement, and manage governance frameworks for AI/ML systems to ensure compliance with regulatory, ethical, and organizational standards.

  • Assess AI/ML models and pipelines for risks such as bias, fairness, privacy, and explainability.

  • Define and enforce AI/ML security policies, controls, and monitoring mechanisms.

• Security Architecture (Azure Focused)

  • Design and maintain secure cloud-based ML/AI solutions on Microsoft Azure.

  • Implement Identity & Access Management (IAM), Key Vault, encryption, and security monitoring for ML workloads.

  • Support compliance with industry standards (ISO, GDPR, HIPAA, SOC2, etc.).

• Governance & Risk Management

  • Establish model governance, monitoring, and audit mechanisms across the ML lifecycle.

  • Conduct risk assessments and threat modeling for AI/ML applications.

  • Collaborate with compliance, risk, and IT security teams to ensure responsible AI adoption.

• Operational Excellence

  • Support incident response and vulnerability management for AI/ML environments.

  • Provide security awareness and governance best practices for AI/ML teams.

  • Document governance frameworks, security policies, and compliance reports.

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Required Skills & Qualifications

• Experience:

  • 2.5+ years of professional experience in AI/ML governance, security, or cloud security architecture.

  • Hands-on experience with AI/ML model lifecycle security (data handling, training, deployment, monitoring).

• Technical Skills:

  • Strong knowledge of Microsoft Azure AI/ML services (Azure ML, Cognitive Services, Synapse).

  • Expertise in Azure Security architecture (Defender, Sentinel, Key Vault, IAM).

  • Understanding of data security, encryption, and compliance frameworks.

  • Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps concepts.

  • Knowledge of Responsible AI principles (bias detection, model explainability, privacy-preserving ML).

• Certifications (Required/Preferred):

  • Microsoft Certified: Azure Security Architect Expert (Required).

  • AI/ML Certification (e.g., Microsoft Certified: Azure AI Engineer Associate, AWS Machine Learning Specialty, or equivalent).

• Soft Skills:

  • Strong analytical and problem-solving skills.

  • Excellent communication and stakeholder management skills.

  • Ability to work cross-functionally with security, compliance, and data science teams.

 

About the Role

We are seeking an AI/ML Governance & Security Specialist with strong expertise in implementing secure and compliant AI/ML solutions. The role will focus on ensuring responsible AI adoption, data security, compliance, and governance across AI/ML projects. The ideal candidate will have hands-on experience in security architecture, cloud platforms (especially Microsoft Azure), and governance frameworks, with proven knowledge of AI/ML lifecycle risks.

---

Key Responsibilities

• AI/ML Security & Governance

  • Design, implement, and manage governance frameworks for AI/ML systems to ensure compliance with regulatory, ethical, and organizational standards.

  • Assess AI/ML models and pipelines for risks such as bias, fairness, privacy, and explainability.

  • Define and enforce AI/ML security policies, controls, and monitoring mechanisms.

• Security Architecture (Azure Focused)

  • Design and maintain secure cloud-based ML/AI solutions on Microsoft Azure.

  • Implement Identity & Access Management (IAM), Key Vault, encryption, and security monitoring for ML workloads.

  • Support compliance with industry standards (ISO, GDPR, HIPAA, SOC2, etc.).

• Governance & Risk Management

  • Establish model governance, monitoring, and audit mechanisms across the ML lifecycle.

  • Conduct risk assessments and threat modeling for AI/ML applications.

  • Collaborate with compliance, risk, and IT security teams to ensure responsible AI adoption.

• Operational Excellence

  • Support incident response and vulnerability management for AI/ML environments.

  • Provide security awareness and governance best practices for AI/ML teams.

  • Document governance frameworks, security policies, and compliance reports.

---

Required Skills & Qualifications

• Experience:

  • 2.5+ years of professional experience in AI/ML governance, security, or cloud security architecture.

  • Hands-on experience with AI/ML model lifecycle security (data handling, training, deployment, monitoring).

• Technical Skills:

  • Strong knowledge of Microsoft Azure AI/ML services (Azure ML, Cognitive Services, Synapse).

  • Expertise in Azure Security architecture (Defender, Sentinel, Key Vault, IAM).

  • Understanding of data security, encryption, and compliance frameworks.

  • Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps concepts.

  • Knowledge of Responsible AI principles (bias detection, model explainability, privacy-preserving ML).

• Certifications (Required/Preferred):

  • Microsoft Certified: Azure Security Architect Expert (Required).

  • AI/ML Certification (e.g., Microsoft Certified: Azure AI Engineer Associate, AWS Machine Learning Specialty, or equivalent).

• Soft Skills:

  • Strong analytical and problem-solving skills.

  • Excellent communication and stakeholder management skills.

  • Ability to work cross-functionally with security, compliance, and data science teams.

 

Job Description:

We are looking for a Site Reliability Engineer with a passion for astronomy and space technology to join our team. In this role, you will work closely with astronomers, astrophysicists, and data scientists to develop, deploy, and manage scalable infrastructure for astronomical data processing, observatory automation, and space research applications.

Key Responsibilities:

• Design, implement, and maintain CI/CD pipelines for astronomical software and data processing workflows.

• Manage and optimize cloud-based infrastructure (AWS, Azure, or Google Cloud) for large-scale space data storage and analysis.

• Automate deployment, scaling, and monitoring of telescope control systems, astrophysics simulations, and satellite operations.

• Collaborate with scientists and engineers to integrate DevOps best practices into astronomical research projects.

• Implement containerization and orchestration (Docker, Kubernetes) for astronomical data pipelines.

• Enhance system reliability, security, and performance for astronomical observatories and space missions.

• Develop and maintain infrastructure as code (Terraform, Ansible, or CloudFormation).

• Monitor and troubleshoot system performance and astronomical data processing jobs.

Requirements:

• Bachelor's or Master’s degree in Computer Science, Astronomy, Astrophysics, or related fields.

• 3+ years of experience in DevOps, SRE, or Cloud Engineering.

• Proficiency in Linux, Shell scripting, Python, or Golang.

• Experience with cloud services (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).

• Knowledge of big data processing (Hadoop, Spark, or Apache Airflow) for handling astronomical datasets.

• Familiarity with astronomical data formats (FITS, HDF5) and scientific computing tools.

• Passion for space exploration, astronomy, or satellite technology.

Preferred Qualifications:

• Experience working with astronomical observatories, space agencies, or research institutes.

• Understanding of radio astronomy, optical telescopes, or space mission software.

• Contributions to open-source projects related to space science or DevOps.

Benefits:

• Work on cutting-edge space and astronomy projects.

• Collaborate with leading scientists and space agencies.

• Competitive salary and flexible work environment.

• Opportunity to contribute to groundbreaking astronomical discoveries.

Build the future of the AI Data Cloud. Join the Snowflake team. Our Sales Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions.   IN THIS ROLE YOU WILL GET TO:

• Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas.
• Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases.
• Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback.
• Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos.
• Influence, tailor and maintain Sales Engineering AI and ML selling assets, including customer presentations, demonstrations, and customer stories.

  ON DAY ONE, WE WILL EXPECT YOU TO HAVE:

• 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud.
• Familiarity and associated knowledge of generative AI techniques like RAG, few shot learning, prompt engineering, or fine-tuning that are used to operationalize enterprise AI use cases like interactive chat applications or text processing.
• Deep knowledge of Python and common ML packages (such as LangChain, pandas, sklearn, and PyTorch) as well as data engineering tools and technologies like dbt, Airflow, and Spark.
• Strong presentation skills to both technical and executive audiences, whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred.

  BONUS POINTS FOR EXPERIENCE WITH THE FOLLOWING:

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, and NeMo-Guard.
• Experience and understanding of large-scale infrastructure-as-a-service platforms (e.g. AWS, Microsoft Azure, GCP, etc.)
• 1+ years of practical Snowflake experience.
• Knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum, etc.)

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.