ML Engineering Consultant

TECHNICAL SKILLS

Must Have

• Advanced SQL
• Amazon AWS Cloud
• Amazon Bedrock
• Amazon SageMaker
• Apache Airflow
• AWS EKS / Kubernetes
• AWS Step Functions
• Certified Python programmer
• CI/CD deployment
• DevOps pipeline experience related to the automation of application testing, delivery, and infrastructure as code (e.g., GitHub, Gradle, Puppet, Terraform, AWS CloudFormation)
• Docker for AWS
• MLOps

Qualifications:

• Advanced degree (Master's or Ph.D.) or equivalent industry experience in Computer Science, Machine Learning, or related fields.
• 5+ years of experience in a similar role in a production environment.
• Experience working with large scale datasets and building ETL pipelines using Spark, Kubeflow, StreamSets, etc.
• Hands-on experience with cloud computing platforms such as AWS.
• Strong proficiency in Python and experience with NLP techniques, resources, and methodologies such as Scikit-learn, TensorFlow, PyTorch, HuggingFace, Comprehend, XGBoost, LangChain, etc.
• Experience integrating machine learning models and data-driven algorithms into larger system architectures that involve pieces like Flask, ElasticSearch, PostgreSQL, IBM MQ, Apache Kafka, etc.
• Experience with iterative development processes, thriving in dynamic and agile environments.
• Ability to own ML delivery tasks end-to-end with little to no direct support.
• Hands-on experience in deploying machine learning models into production environments.