About Truelogic
At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.
Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.
By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.
Our Client
Our client is a forward-thinking company revolutionizing the rental experience by leveraging AI and data-driven solutions. They specialize in simplifying the journey for renters by curating personalized property matches based on individual preferences and lifestyles. Committed to innovation, they aim to make renting stress-free and seamless for all.
Job Summary
We are seeking an experienced ML Ops Engineer to build and optimize the infrastructure powering machine learning operations within a dynamic and collaborative environment. This role involves designing robust data pipelines, automating CI/CD workflows for ML models, and implementing scalable, reproducible systems that enable seamless deployment and monitoring. Join us to shape the future of AI-driven solutions!
Responsibilities
Build and manage automated, reproducible ML pipelines for data ingestion, training, validation, deployment, and monitoring.
Develop scalable model-serving architectures, including containerized deployments, APIs, and real-time frameworks.
Automate infrastructure workflows, establishing CI/CD pipelines for ML models with robust versioning and rollback mechanisms.
Monitor model performance and data drift in production, ensuring accuracy and system health.
Collaborate with cross-functional teams to promote best practices for ML reproducibility, scalability, and maintenance.
Qualifications and Job Requirements
5+ years of experience in ML Ops, Data Engineering, or DevOps roles.
Proficiency with cloud platforms such as GCP, AWS, or Azure, and ML Ops tools like Kubeflow, MLflow, or SageMaker.
Expertise in containerization (Docker, Kubernetes) and CI/CD pipelines (GitLab CI, Jenkins, CircleCI).
Hands-on experience with data pipeline orchestration tools like Airflow.
Strong knowledge of data versioning, feature stores, and model lifecycle management.
What We Offer
100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection.
Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.
Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed.
Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.
Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.
Why You’ll Like Working Here
A Culture That Values You: We prioritize well-being and work-life balance, offering engagement activities and fostering dynamic teams to ensure you thrive both personally and professionally.
Diverse, Global Network: Connect with over 600 professionals in 25+ countries, expand your network, and collaborate with a multicultural team from Latin America.
Team Up with Skilled Professionals: Join forces with senior talent. All of our team members are seasoned experts, ensuring you're working with the best in your field.
Apply now!
