3 results for Qa Automation Engineer in Providence, RI

M365 Implementation Engineer

Seekonk, MA
remote
Permanent
120000 - 140000 USD / Yearly
M365 Implementation EngineerLocation: RemoteDepartment: Professional ServicesType: Full-Time About the RoleWe are seeking an experienced M365 Implementation Engineer to join our Professional Services team. This position combines hands-on engineering work with frequent client interaction. You will design, deploy, and optimize Microsoft 365 solutions while collaborating directly with customers through daily video calls, workshops, and project updates.This role is ideal for someone who enjoys both the technical side of M365 and the client-facing aspects of consulting. What You’ll Do<ul><li>Lead the deployment, configuration, and migration of Microsoft 365 services in client environments.</li><li>Deliver solutions across collaboration, communication, and cloud productivity platforms within the M365 ecosystem.</li><li>Meet with clients regularly through video calls to gather requirements, present progress, and provide technical guidance.</li><li>Develop automated workflows, apps, and dashboards using the Power Platform to streamline business processes.</li><li>Implement best practices around identity, governance, compliance, and security within the M365 tenant.</li><li>Troubleshoot escalated issues and support clients throughout project delivery.</li><li>Work closely with project managers and stakeholders to translate requirements into effective technical solutions.</li></ul>
2026-03-10T00:00:00Z

Senior Machine Learning Engineer

Boston, MA
remote
Permanent
180000 - 200000 USD / Yearly
We are looking for a highly experienced Senior Machine Learning Engineer to join our team in Boston, Massachusetts. In this role, you will design, develop, and deploy cutting-edge machine learning systems that solve complex problems and scale effectively in production environments. This position offers an exciting opportunity to contribute to impactful projects, leveraging your expertise in machine learning, cloud infrastructure, and data engineering. Responsibilities: • Build and deploy machine learning models and solutions for production environments, ensuring they meet scalability and performance standards. • Design and implement comprehensive ML pipelines, including data ingestion, feature engineering, model training, evaluation, and serving. • Write clean, efficient code in Python and leverage its ML ecosystem, such as TensorFlow, PyTorch, and scikit-learn. • Work with large datasets to extract meaningful insights and develop complex queries using modern data processing tools. • Utilize containerization technologies like Docker and cloud platforms such as AWS to ensure robust and scalable deployment. • Apply MLOps best practices, including CI/CD pipelines, automated testing, and performance monitoring, to maintain reliable machine learning systems. • Conduct research and apply deep machine learning and AI techniques, including statistical modeling and large language models. • Solve complex analytical problems with pragmatic engineering approaches while maintaining scientific rigor. • Collaborate with cross-functional teams to align machine learning solutions with business goals and mission-driven objectives. • Monitor and address issues like data drift and model performance to ensure continuous improvement and reliability.
2026-03-10T00:00:00Z

DevOps Engineer

Westborough, MA
onsite
Temporary
50 - 55 USD / Hourly
We are looking for a skilled DevOps Engineer to join our team in Westborough, Massachusetts. In this long-term contract role, you will play a pivotal part in enhancing the reliability and scalability of cloud infrastructure, CI/CD pipelines, and deployment strategies. The position requires a hybrid schedule, with in-office work on Tuesdays, Wednesdays, and Thursdays. Responsibilities: • Design, build, and maintain robust CI/CD pipelines using tools such as GitHub Actions, Jenkins, and Ansible. • Develop and implement standardized deployment pipelines for applications, integration platforms like MuleSoft, and cloud infrastructure. • Manage cloud environments using Infrastructure as Code (IaC) technologies, including Terraform and Helm. • Support containerized platforms and Kubernetes-based systems, including Docker. • Collaborate with development teams to improve automation processes, deployment frequency, and platform reliability. • Apply best practices for version control, secrets management, artifact repositories, and environmental consistency. • Troubleshoot and resolve issues across pipelines, applications, and infrastructure layers to ensure operational stability. • Enhance monitoring, logging, and observability tools to optimize platform performance. • Partner with cross-functional teams to streamline DevOps practices for custom applications and backend services. • Maintain detailed technical documentation and uphold high standards for follow-up and organizational timelines.
2026-03-20T00:00:00Z