Senior ML Engineer (contract)
We are seeking a Senior Machine Learning Engineer to design, deploy, and optimize machine learning model infrastructure using Databricks, Azure, and related technologies. This role involves managing the end-to-end lifecycle of ML models, collaborating with cross-functional teams, and ensuring secure, efficient, and scalable ML operations.
Key Responsibilities
ML Models Hosting Technical Architecture:
• Design and implement data storage solutions using ADLS and related technologies.
• Build and maintain model training environments with Databricks.
• Optimize model run-time and latency for on-demand workloads.
• Create and manage APIs for model serving.
• Architect and enforce robust ML model security.
Creation, Training, And Serving Of ML Models
• Develop and deploy models using Databricks notebooks.
• Manage code and versioning using GitLab.
• Implement batch processing pipelines and real-time inference deployments.
• Collaborate with data engineers and scientists for production integration.
Collaboration And Communication
• Partner with stakeholders to understand requirements and translate them into technical ML solutions.
• Document processes, models, and architecture for long-term maintainability.
• Stay up to date on the latest advancements in ML and data engineering.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Proven hands-on experience in ML engineering across creation, training, and deployment.
• Expertise with Databricks, Unity Catalog, ADLS, and notebooks.
• Proficiency with GitLab version control and API development.
• Deep understanding of ML security and data protection.
• Strong problem-solving and documentation skills.
• Excellent verbal and written communication abilities.
Preferred Qualifications
• Experience with Azure cloud platform.
• Familiarity with Apache Spark or similar big data tools.
• Working knowledge of Docker and Kubernetes.
Skills Summary
Core Expertise:
Machine Learning lifecycle management, MLOps, real-time and batch ML deployments, model performance optimization
Languages & Frameworks
Python, Databricks Notebooks, API development frameworks
Cloud & Containerization
Azure, Docker, Kubernetes
ML & Data Tools
Databricks, ADLS, Unity Catalog, Apache Spark
DevOps & CI/CD
GitLab, model versioning, secure deployment pipelines
Other Tools & Technologies
SQL, batch data pipelines, API gateways, real-time inference tools
Soft Skills
Strong communication, stakeholder collaboration, documentation, analytical thinking, cross-functional teamwork
The pay range that the employer in good faith reasonably expects to pay for this position is $38.37/hour - $59.95/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis. Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.
We are seeking a Senior Machine Learning Engineer to design, deploy, and optimize machine learning model infrastructure using Databricks, Azure, and related technologies. This role involves managing the end-to-end lifecycle of ML models, collaborating with cross-functional teams, and ensuring secure, efficient, and scalable ML operations.
Key Responsibilities
ML Models Hosting Technical Architecture:
• Design and implement data storage solutions using ADLS and related technologies.
• Build and maintain model training environments with Databricks.
• Optimize model run-time and latency for on-demand workloads.
• Create and manage APIs for model serving.
• Architect and enforce robust ML model security.
Creation, Training, And Serving Of ML Models
• Develop and deploy models using Databricks notebooks.
• Manage code and versioning using GitLab.
• Implement batch processing pipelines and real-time inference deployments.
• Collaborate with data engineers and scientists for production integration.
Collaboration And Communication
• Partner with stakeholders to understand requirements and translate them into technical ML solutions.
• Document processes, models, and architecture for long-term maintainability.
• Stay up to date on the latest advancements in ML and data engineering.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Proven hands-on experience in ML engineering across creation, training, and deployment.
• Expertise with Databricks, Unity Catalog, ADLS, and notebooks.
• Proficiency with GitLab version control and API development.
• Deep understanding of ML security and data protection.
• Strong problem-solving and documentation skills.
• Excellent verbal and written communication abilities.
Preferred Qualifications
• Experience with Azure cloud platform.
• Familiarity with Apache Spark or similar big data tools.
• Working knowledge of Docker and Kubernetes.
Skills Summary
Core Expertise:
Machine Learning lifecycle management, MLOps, real-time and batch ML deployments, model performance optimization
Languages & Frameworks
Python, Databricks Notebooks, API development frameworks
Cloud & Containerization
Azure, Docker, Kubernetes
ML & Data Tools
Databricks, ADLS, Unity Catalog, Apache Spark
DevOps & CI/CD
GitLab, model versioning, secure deployment pipelines
Other Tools & Technologies
SQL, batch data pipelines, API gateways, real-time inference tools
Soft Skills
Strong communication, stakeholder collaboration, documentation, analytical thinking, cross-functional teamwork
The pay range that the employer in good faith reasonably expects to pay for this position is $38.37/hour - $59.95/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis. Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.
