ML Ops Engineer

Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions. Key Responsibilities Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.Automate model training, testing, deployment, and monitoring in cloud environments (e.g., Google Cloud Platform, AWS, Azure).Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining.Monitor model performance using observability tools and

Job Title: AI/ML Ops Engineer Sanity Check (NVIDIA) Location: Charlotte, NC (Onsite) Job Summary We are seeking an experienced AI/ML Ops Engineer with strong expertise in NVIDIA GPU environments, AI/ML infrastructure, and sanity testing/validation processes. The ideal candidate will support deployment, monitoring, and operational validation of AI/ML workloads while ensuring system performance, stability, and reliability across GPU-based platforms. Key Responsibilities Perform sanity checks an

10+ Years of professional experience in Software Engineering & 3+ Years in AIML, Machine Learning Model Operations.Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).Experience with cloud platforms and containerization (Docker, Kubernetes).Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks.Solid understanding of software engineering principles and DevOps practices.Ability to communicate complex technic

Location: Charlotte, NC Salary: $69.00 USD Hourly - $74.00 USD Hourly Description: Senior Software Engineer - Data Engineering (Google Cloud Platform & AI) Location: Charlotte, NC (Preferred) 300 S Brevard St, Charlotte, NC1525 W T Harris Blvd, Charlotte, NC Work Model: Hybrid (3 days onsite) Employment Type: Contract (12 months, with expected extension) About the Role We are looking for a Senior Software Engineer specializing in Data Engineering to design and build scalable data platform