Salesforce Developer

Terraform Vertex AI Pipelines Operations Automation Mentorship Governance Kubernetes TensorFlow Scalability Data Science Communication Observability AWS SageMaker Data Ingestion Microsoft Azure Computer Science Machine Learning Data Engineering Docker (Software) Platform Agnostic Business Valuation Amazon Web Services Feature Engineering Software Engineering Technology Ecosystems Full Stack Development Stakeholder Management Distributed Data Store Azure Machine Learning Artificial Intelligence Business Transformation Cloud-Native Infrastructure Infrastructure as Code (IaC) Python (Programming Language) Scikit-Learn (Python Package) PyTorch (Machine Learning Library) MLOps (Machine Learning Operations) Artificial Intelligence Development Scalable Machine Learning Infrastructure, We are seeking a Senior MLOps Engineer to design, build, and scale enterprise-grade machine learning platforms that support the full AI/ML lifecycle. This role requires a hands-on technical leader who can architect robust MLOps solutions while partnering with data scientists, software engineers, and business stakeholders to bring machine learning models into production.

The ideal candidate has extensive experience building end-to-end MLOps ecosystems, implementing cloud-native infrastructure, and creating scalable environments that accelerate AI development and deployment., * Design and implement end-to-end MLOps platforms supporting data ingestion, feature engineering, model training, model registry, deployment, and monitoring.

• Develop and maintain scalable machine learning infrastructure in cloud environments.
• Build and optimize CI/CD pipelines for ML workloads and model deployment.
• Deploy and manage Kubernetes-based environments, including GPU-enabled clusters.
• Implement Infrastructure as Code (IaC) standards using Terraform.
• Partner with data science teams to operationalize machine learning solutions.
• Establish monitoring, observability, governance, and model performance tracking.
• Create scalable and reliable distributed data processing pipelines.
• Drive platform standardization, automation, and best practices across AI initiatives.
• Communicate technical solutions and recommendations to both technical and non-technical stakeholders., Terraform Vertex AI Pipelines Operations Automation Mentorship Governance Kubernetes TensorFlow Scalability Data Science Communication Observability AWS SageMaker Data Ingestion Microsoft Azure Computer Science Machine Learning Data Engineering Docker (Software) Platform Agnostic Business Valuation Amazon Web Services Feature Engineering Software Engineering Technology Ecosystems Full Stack Development Stakeholder Management Distributed Data Store Azure Machine Learning Artificial Intelligence Business Transformation Cloud-Native Infrastructure Infrastructure as Code (IaC) Python (Programming Language) Scikit-Learn (Python Package) PyTorch (Machine Learning Library) MLOps (Machine Learning Operations) Artificial Intelligence Development Scalable Machine Learning Infrastructure +0

Google IT Automation with Python

• End-to-end MLOps platform architecture (data ingestion, feature stores, model training, registry, deployment, monitoring)
• Expert-level experience with AWS, Azure, or GCP ML services (SageMaker, Azure ML, Vertex AI)
• Kubernetes, Docker, and Terraform (Infrastructure as Code)
• Strong Python development experience with PyTorch, TensorFlow, and/or scikit-learn
• Experience building and supporting distributed data and machine learning pipelines
• Strong communication skills and ability to work independently, * 8+ years of software engineering, machine learning engineering, data engineering, or related experience.
• 4+ years of experience designing and implementing end-to-end MLOps platforms.
• Advanced proficiency in Python.
• Hands-on experience with PyTorch, TensorFlow, scikit-learn, or similar ML frameworks.
• Deep expertise in at least one major cloud platform (AWS, Azure, or GCP) and associated machine learning services.
• Strong experience with Kubernetes, Docker, and Terraform.
• Experience building and supporting distributed data processing and machine learning pipelines.
• Excellent communication, collaboration, and stakeholder management skills.
• Demonstrated ability to work independently and lead technical initiatives.

Education & Experience

• PhD or Master's Degree in Computer Science, Engineering, or a related quantitative field

OR

• Bachelor's Degree in Computer Science, Engineering, or a related quantitative field and at least 2 years of relevant experience

OR

• 15+ years of comparable professional experience in lieu of a degree

Preferred Qualifications

• Experience supporting large-scale production AI/ML environments.
• Background implementing governance, security, and compliance standards for ML platforms.
• Experience mentoring engineers and driving technical best practices.
• Familiarity with feature stores, model registries, and ML observability tools.
• Experience optimizing infrastructure for performance, scalability, and cost efficiency.

This is a Contract to Hire position based out of Raleigh, NC. Pay and Benefits

The pay range for this position is $50.00 - $65.00/hr.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following: * Medical, dental & vision * Critical Illness, Accident, and Hospital * 401(k) Retirement Plan - Pre-tax and Roth post-tax contributions available * Life Insurance (Voluntary Life & AD&D for the employee and dependents) * Short and long-term disability * Health Spending Account (HSA) * Transportation benefits * Employee Assistance Program * Time Off/Leave (PTO, Vacation or Sick Leave) Workplace Type

We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company., We're a leading provider of business and technology services. We accelerate business transformation for our customers. Our expertise in strategy, design, execution and operations unlocks business value through a range of solutions. We're a team of 80,000 strong, working with over 6,000 customers, including 80% of the Fortune 500 across North America, Europe and Asia, who partner with us for our scale, full-stack capabilities and speed. We're strategic thinkers, hands-on collaborators, helping customers capitalize on change and master the momentum of technology. We're building tomorrow by delivering business outcomes and making positive impacts in our global communities. TEKsystems and TEKsystems Global Services are Allegis Group companies. Learn more at TEKsystems.com.