Senior ML + DevOps Engineer - Advertising (Mexico) at Truelogic

, , Mexico -

Full Time

Start Date

Immediate

Expiry Date

22 Dec, 25

Salary

0.0

Posted On

23 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, Python, FastAPI, Cloud Infrastructure, Docker, Terraform, CI/CD, Data Transformation, Monitoring, Troubleshooting, Machine Learning, Production Systems, Observability, Logging, ETL, Multithreading

Industry

Information Technology & Services

Description

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 A global digital transformation network that blends creativity and engineering at scale. With teams spanning design, development, and AI innovation, they help major enterprises navigate changing consumer behaviors, emerging technologies, and the future of digital experiences. Their work pushes the boundaries of storytelling, publishing, and customer engagement across industries. Job Summary We are seeking a Senior ML+DevOps Engineer to architect and scale AI/ML infrastructure for next-generation digital experiences. This role is central to building robust, production-grade MLOps pipelines, ensuring seamless deployment, monitoring, and optimization of machine learning models. The ideal candidate brings deep expertise in Python, containerization, and cloud platforms, with hands-on experience delivering end-to-end MLOps solutions. You will collaborate closely with data scientists, engineers, and product teams to power AI-driven publishing technologies, content automation, and intelligent pipelines. Responsibilities Design and implement end-to-end MLOps pipelines for training, deployment, and inference. Build and maintain Python-based APIs (FastAPI) to support ML workflows and data ingestion. Configure and manage cloud infrastructure (AWS, GCP, Azure) to support AI/ML workloads. Automate deployment, scaling, and monitoring of models using Docker and CI/CD pipelines. Implement observability, logging, and alerting with tools like CloudWatch, Prometheus, Grafana, and GCP logging. Collaborate with cross-functional teams to define requirements and deliver scalable MLOps solutions. Optimize model performance and system reliability while troubleshooting production issues. Apply infrastructure-as-code practices (Terraform) for reproducible and maintainable deployments. Stay ahead of industry best practices in MLOps, cloud-native engineering, and AI/ML integration. Qualifications and Job Requirements Proven experience designing and implementing end-to-end MLOps pipelines for model training and inference. Advanced Python expertise, including multithreading, async/await, multiprocessing, and parallelism. Experience building and deploying APIs with FastAPI for data ingestion and ML workflows. Strong background in data cleaning, transformation, and ETL processes using Python. Hands-on experience with Terraform (including production usage and state file management). Expertise in Docker, including container packaging and entry point customization. Experience monitoring and troubleshooting production ML models with S3, GCP logging, CloudWatch, Prometheus, or Grafana. Proficiency with CI/CD pipelines (preferably GitHub Actions). 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!

Responsibilities

The Senior ML+DevOps Engineer will design and implement end-to-end MLOps pipelines for training, deployment, and inference. This role involves building robust infrastructure to support AI/ML workloads and collaborating with cross-functional teams to optimize model performance.