Position: Senior ML Engineer with WMS/Logistics
Location: Atlanta, GA or Remote
Duration: 6 - 12 Months
Job Description
Look for Senior profiles (8+ years)
Core Job Responsibilities:
• Develop end-to-end ML pipelines encompassing the ML lifecycle from data ingestion, data transformation, model training, model validation, model serving, and model evaluation over time.
- Collaborate closely with AI scientists to accelerate productionization of ML algorithms.
- Setup CI/CD/CT pipelines, model repository for ML algorithms
- Deploy models as a service both on-cloud and on-prem.
- Learn and apply new tools, technologies, and industry best practices.
Key Qualifications
- MS in Computer Science, Software Engineering, or equivalent field
• Experience with Cloud Platforms, especially GCP and related skills: Docker, Kubernetes, edge computing
- Familiarity with task orchestration tools such as MLflow, Kubeflow, Airflow, Vertex AI, Azure ML, etc.
- Fluency in at least one general purpose programming language. Python - Required
- Strong skills in the following: Linux/Unix environment, testing, troubleshooting, automation, Git, dependency management, and build tools (GCP Cloud Build, Jenkins, Gitlab CI/CD, Github Actions, etc.).
- Data engineering skills are a plus, such as Beam, Spark, Pandas, SQL, Kafka, GCP Dataflow, etc.
- 5+ years of experience, including academic experience, in any of the above.
Job Type: Contract
Pay: $45.00 - $50.00 per hour
Expected hours: 8 per week
Experience level:
- 10 years
- 11+ years
- 5 years
- 6 years
- 7 years
- 8 years
- 9 years
Schedule:
Education:
Experience:
- Logistics: 1 year (Preferred)
- warehouse: 1 year (Preferred)
- Machine learning libraries: 5 years (Preferred)
- ML: 5 years (Required)
- WMS: 5 years (Required)
Ability to Commute:
Work Location: Remote