Machine Learning DevSecOps Engineer

Encontrado en: Talent MX C2 - hace 3 semanas

Mexico City Ford Motor Company A tiempo completo

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow’s transportation.

Global Data Insight & Analytics organization is looking for a Machine Learning Engineer focused on building and driving the strategy forward for our internal Data Science / AI/ML platform. This role will work in a small, cross-functional team. The position will collaborate directly and continuously with other engineers, business partners, product managers and designers, and will release early and often. 

Work closely with Tech Anchor, Product Manager and Product Owner to deliver MLOPs platform in GCP using Python and other tools for the data scientists across the company. Help innovate standardize machine learning development practices.  Experiment, innovate and share knowledge with the team. Lead by example in use of Paired Programming for cross training/upskilling, problem solving, and speed to delivery. Leverage latest ML/NLP/ GCP/AIOPs/Kubernetes technologies. Design and develop innovative ML models and software algorithms to solve complex business problems in both structured and unstructured environments. Use machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. Train and re-train ML models and systems as required. Deploy ML models and algorithms into production and run simulations for algorithm development and test various scenarios. Automate model deployment, training and re-training, leveraging principles of agile methodology, CI/CD/CT (Continuous Integration/ Continuous Deployment/ Continuous Training) and MLOps. Enable model management for model versioning and traceability.

Minimum Qualifications

English proficiency (written and verbal) A Bachelor’s degree in Computer Science / Computer Engineering or similar technical discipline.  2+ years of experience with Python and Cloud Engineering / Services such as GCP Vertex AI and related services. Experience with ML workflow orchestration tools: , Airflow, Kubeflow etc.  Experience in DevSecOps using tools such as Jenkins/Tekton, Checkmarx etc. Experience in container management solution: ., Kubernetes, Docker, GKE. Experience in scripting language: ., Bash, PowerShell etc. 

Desired Skills

Masters in Computer Science / Machine Learning or related field. Experience with Terraform. Experience in software craftsmanship practices such as Paired Programming, Test Driven Development. Understanding of MLOPs/Machine Learning Life Cycle and common machine learning frameworks: Sklearn, Tensorflow, Pytorch etc. is a big plus. Experience applying Agile practices to solution delivery. Knowledge of GenAI technologies and concepts.

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