Engineering Manager, Applied AI & Machine Learning Engineering

Tasks

• Build and maintain data pipelines
• Communicate technical context to different audiences
• Deliver AI ML roadmap items on time
• Design ML model solutions and services
• Lead machine learning engineering execution
• Maintain AI ML solutions and documentation
• Oversee AI ML lifecycle from research to deployment
• Own machine learning services for other teams
• Provide technical direction and mentorship
• Remove roadblocks and improve engineering processes

Perks/Benefits

• Corporate library access
• Flexible schedule
• Fully remote work
• Licensed software
• Performance and merit reviews
• Professional development plans
• Provided laptop
• Public speaking support
• Referral bonus program

Skills/Tech-stack

AWS Glue | Amazon Kinesis | Amazon SNS | Amazon SQS | Apache Airflow | Apache Kafka | Apache Spark | Artificial Intelligence | Cloud Computing | Cloud Dataflow | Data Engineering | Data Lake | Data Pipelines | Data Warehouse | Docker | Embeddings | Generative AI | Google Cloud | Google Cloud Dataflow | Keras | Kubernetes | LLM | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Microservices | Natural Language | Natural Language Processing | Pandas | PyTorch | Python | SQL | Scikit-learn | Snowflake | System design | Vector Databases