Machine Learning Engineer Full Time

Summary:

• Veeam is the #1 global market leader in data protection and ransomware recovery, empowering organizations to bounce forward from data outages.
• The company provides radical resilience through data security, recovery, and freedom for hybrid cloud environments.
• Veeam’s Data Platform offers a unified solution for cloud, virtual, physical, SaaS, and Kubernetes environments.
• Headquartered in Seattle, with offices in over 30 countries, Veeam serves 450,000 customers, including 74% of the Global 2000.

Responsibilities:

• Design, build, and refine machine learning models for various use cases such as ransomware detection, backup data classification, and conversational AI.
• Implement scalable and reproducible ML pipelines on Azure, using managed services like Azure Fabric, Azure Machine Learning, Azure Data Lake Service, Azure Data Factory, Databricks, and Snowflake.
• Integrate models into production services with robust monitoring, logging, and automated CI/CD (MLOps) practices for continuous improvement and rapid iteration.
• Collaborate with data engineers to define data architectures and managed services that facilitate efficient model training and inference.
• Continuously optimize ML models by applying feature selection, engineering, dimensionality reduction, and benchmarking to enhance accuracy, latency, and scalability.
• Implement model quality checks, bias detection, and model explainability frameworks to maintain ethical and transparent AI standards.
• Work with product managers, UX designers, and stakeholders to translate business requirements into technical ML solutions.
• Educate and mentor team members, data scientists, and engineers on ML best practices, frameworks, and toolsets.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, Machine Learning, or a related field.
• Proven experience building and deploying ML models in production using Python and popular ML frameworks like TensorFlow, PyTorch, and scikit-learn.
• Hands-on experience with modern ML tools and services such as Azure Fabric, Azure ML Studio, Azure Data Lake, Databricks, Snowflake, and similar services.
• Strong knowledge of MLOps principles, data governance best practices, CI/CD pipelines, containerization (Docker), orchestration (Kubernetes), and networking.
• Familiarity with anomaly detection, time series analysis, and/or NLP.
• Strong statistical knowledge, including hypothesis testing, regression analysis, and model evaluation metrics.
• Ability to break down broad problems into smaller, well-defined components, addressing uncertainties as needed.
• Excellent communication and interpersonal skills, with the ability to explain complex ML concepts to both technical and non-technical stakeholders.
• Self-driven, detail-oriented, and eager to work in a fast-paced, dynamic environment within a larger organization.

Benefits:

• Medical, dental, and vision insurance, with 100% company-paid employee premiums.
• Unlimited Paid Time Off (PTO).
• Life and Disability Insurance.
• Veeam Care Days – additional 24 hours for volunteering activities.
• Professional training, courses, internal meetups, and unlimited access to online learning platforms (Percipio, Athena, O’Reilly).
• Mentoring through the MentorLab program.