AI and ML Engineer L4
Location: Detroit, MI
We are seeking an innovative AI/ML Engineer to design, develop, and implement cutting-edge artificial intelligence and machine learning solutions. In this role, you will leverage Google's suite of AI products and technologies to create intelligent systems that solve complex business problems. You will work closely with cross-functional teams to integrate AI capabilities into our products and services.
This role requires a deep understanding of AI/ML principles, software development practices, and Google's AI technologies. The ideal candidate will have a proven track record of developing and deploying AI solutions using Google's ecosystem of tools and services. They should be passionate about staying current with Google's rapidly evolving AI landscape and capable of applying these cutting-edge technologies to solve real-world business problems.
- Strong programming skills in Python, and familiarity with Java or C++
- Solid understanding of machine learning algorithms and techniques
- Experience with deep learning frameworks (TensorFlow preferred)
- Familiarity with Google Cloud Platform (GCP) and its AI/ML services
- Knowledge of data processing and analysis techniques
- Strong analytical and problem-solving skills
- Excellent communication and collaboration abilities
Level 4 (10-14 years of experience):
- Designs scalable, production-grade AI systems using Google Cloud technologies
- Implements cutting-edge ML techniques (e.g., few-shot learning, meta-learning)
- Develops custom AI solutions using Google's open-source tools (e.g., JAX, Flax)
- Utilizes Google Cloud TPUs for high-performance model training
- Implements advanced MLOps practices, including ML pipelines and continuous training
- Leads initiatives for adopting Google's AI technologies across the organization
Technical Skills:
- Google Cloud AI/ML Services: AI Platform, Vertex AI, AutoML, BigQuery ML
- TensorFlow Ecosystem: TensorFlow, Keras, TensorFlow Extended (TFX), TensorFlow.js
- Google AI APIs: Vision AI, Natural Language AI, Translation AI, Speech-to-Text, Text-to-Speech
- Google Cloud Data Tools: Dataflow, Dataprep, Data Fusion, Pub/Sub
- MLOps on Google Cloud: AI Platform Pipelines, Kubeflow
- Google's Responsible AI Practices and Tools
- Familiarity with Google's open-source AI projects (e.g., BERT, T5, JAX)
- Experience with Google Cloud TPUs and distributed training
- Knowledge of Google's AI research initiatives and latest publications