Job
Description
As an MLOps Architect at ORBCOMM, you will play a crucial role in designing and implementing the technology architecture that facilitates the deployment, scaling, and management of Generative AI and machine learning models. Your responsibilities will include: - Architecting end-to-end infrastructure and reference architectures for deploying GenAI and ML models into production environments. - Defining best practices for packaging, APIs, containerization, and Infrastructure-as-Code (IaC) patterns to enable modular and reusable deployment frameworks. - Designing and building pipelines for model training, validation, deployment, rollback, and monitoring. - Supporting both batch and real-time inference workloads, optimizing for cost, performance, and reliability. - Establishing monitoring, alerting, and drift detection mechanisms to maintain model health and detect anomalies. - Automating workflows through CI/CD and continuous training pipelines, versioning, and automated testing of models. - Collaborating with data scientists, product, and IT teams to integrate models and iterate on production insights. - Optimizing infrastructure for reliability, GPU/TPU utilization, and cost efficiency. - Ensuring governance, compliance, and responsible AI practices, including model version control, security, bias mitigation, and regulatory standards. Qualifications required for this role include: - Holding a bachelor's degree (or equivalent experience) in Computer Science, Engineering, or a related field. - Bringing 7+ years of experience in software engineering, DevOps, or cloud infrastructure, with at least 3 years focused on AI/ML deployment. - Having hands-on expertise in one or more cloud platforms (AWS, Azure, or GCP) and container orchestration (Docker, Kubernetes). - Proficiency with MLOps frameworks and tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks. - Strong coding skills (Python preferred) and familiarity with APIs, CI/CD, data pipelines, and automation. - Solid understanding of Generative AI, large language models (LLMs), embeddings, and vector databases (or a willingness to learn quickly). Preferred qualifications for the MLOps Architect role at ORBCOMM include: - Master's degree in Computer Science, Data Engineering, or a related area. - Experience deploying and scaling LLM or GenAI applications in production environments. - Knowledge of model drift detection, bias mitigation techniques, and frameworks for Responsible AI. - Experience working in regulated or security-sensitive environments is a plus. At ORBCOMM, you will be part of a team of pioneers in IoT technology, driving innovation and empowering clients to make data-driven decisions. With a comprehensive solution portfolio and over 30 years of experience, we manage millions of assets worldwide across diverse sectors. If you are seeking a thrilling career opportunity in a vibrant, growth-oriented environment, ORBCOMM is the perfect fit for you.,
