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since 2014, we have been dedicated to breaking down global barriers and accelerating the future of work for both technologists and organizations around the world.
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this is a fully remote opportunity for one of our esteemed clients.
we are seeking a highly skilled machine learning engineer to support our client's growing ai-driven traffic analysis platform.
this role will be pivotal in handling large-scale video processing pipelines, model execution, and automation of end-to-end machine learning workflows.
key responsibilities develop, optimize, and maintain end-to-end data pipelines for processing large-scale video data (e.g.
: mp4 files) implement and optimize model training, execution, and inference workflows for computer vision models design and manage aws-based infrastructure using infrastructure-as-code (terraform) develop and maintain lambda functions and other aws serverless components to automate data pipelines utilize python for data processing, etl workflows, and orchestration of ml tasks manage and optimize aws auto-scaling, ensuring efficient deployment and performance of workloads work with containerization technologies (ecs/kubernetes) to deploy and scale ai applications ensure continuous automation and streamlining of data processing pipelines to meet slas for client deliverables collaborate closely with data scientists and other engineers to ensure seamless integration of models into production workflows perform validation and monitoring of ml model outputs, ensuring accuracy and performance required qualifications proficiency in python and experience working with ml model training & inference execution strong background in aws services, including lambda, ecs/k8s, s3, cloudwatch, and auto-scaling mechanisms expertise in infrastructure-as-code (terraform) for provisioning and managing cloud resources experience with containerization (docker, ecs, kubernetes) for deploying scalable applications strong knowledge of data pipeline orchestration, automation, and optimization experience handling large-scale unstructured video data processing ability to quickly adapt and implement new ai models into production workflows familiarity with yolo (you only look once) models or other computer vision frameworks (e.g., roboflow, opencv preferred but not required) nice-to-have qualifications experience working in computer vision applications for traffic analysis or similar domains familiarity with real-time data streaming previous experience in a fast-paced startup environment soft skills & work culture fit self-motivated and able to work independently in a remote setting strong problem-solving skills and ability to troubleshoot ml pipeline issues excellent communication skills to collaborate effectively with remote teams comfortable with quick iteration cycles and ability to pivot based on business needs experience working in small, fast-moving teams where agility and efficiency are key overlap hours: 6-8 hours with est (8 hours highly preferred) required skills python (4 - 6 yrs) aws (amazon web services) (2 - 3 yrs) docker (2 - 3 yrs) terraform (2 - 3 yrs) computer vision (2 - 3 yrs) optional skills must have: python, computer vision (yolo), aws (lambda), ml pipelines, docker, kubernetes, terraform.
time zone overlap requirements: fully overlap with utc –5 location requirements: working hours: full-time dedication (8 hours/day - 40 hours/week) offer full-time dedication (40 hours/week) at andela, we know our strengths lie in our diverse community whose talents, perspectives, backgrounds, and orientations we take pride in.
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come as you are.
seniority level mid-senior level employment type contract job function information technology technology, information and media #j-18808-ljbffr