Looking for a Machine Learning Engineer focused on building and driving the strategy forward for our internal Data Science / AI/ML platform. Collaborate directly and continuously with other engineers, business partners, product managers and designers, and will release early and often.
Responsibilities:
The team you will be working on is focused on building Mach1ML platform - an AI/ML enablement platform to democratize Machine Learning across enterprises (like Uber's Michelangelo, Facebook's FBLearner, etc.).
Work closely with Tech Anchor, Product Manager and Product Owner to deliver MLOPs platform and Gen AI solution in GCP using Python and other tools for the data scientists and business across the company.
Work with software and ML engineers/Data Scientist to tackle challenging AIOps problems.
Maintain and manage current CI/CD ecosystem and tools.
Find ways to automate and continually improve current CI/CD processes and release processes.
Examine, inspect codes / scripts, and resolve issues.
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/Gen AI / GCP/AIOPs/Kubernetes technologies.
Experience Required:
A bachelor's degree in computer science / computer engineering or similar technical discipline.
2+ years of experience with Cloud Engineering / Services.
3+ years of work experience as a backend software engineer in Python with exceptional software engineering knowledge.
Experience with ML workflow orchestration tools: Airflow, Kubeflow etc.
Advanced working knowledge of object-oriented/object function programming languages: Python, C/C++, Julia
Experience in DevOps: Jenkins/Tekton etc.
Experience with cloud services, preferably GCP Services like Vertex AI, Cloud Function, BigQuery etc.
Experience in container management solution: Kubernetes, Docker.
Experience in scripting language: Bash, PowerShell etc.
Experience with Infrastructure as code: Terraform etc.
Skills Preferred:
Master focused on Computer Science / Machine Learning or related field.
Experience working with Google Cloud platform (GCP) - specifically Google Kubernetes engine, Terraform, and infrastructure.
Experience in delivering cloud engineering products.
Experience in programming concepts such as Paired Programming, Test Driven Development, etc.
Understanding of MLOPs/Machine Learning Life Cycle and common machine learning frameworks: sklearn, TensorFlow, pytorch etc. is a big plus.
Must be a quick learner and open to learning new technology.
Experience applying agile practices to solution delivery.
Experience in all phases of the development lifecycle.
Must be team-oriented and have excellent oral and written communication skills.
Good organizational and time-management skills.
Must be a self-starter to understand existing bottlenecks and come up with innovative solutions.
Knowledge of coding and software craftsmanship practices.
Experience and good understanding of GCP processing /DevOPs/ Machine Learning