Software Engineer

Summary

Join Strong Analytics as a Machine Learning Engineer to design and develop machine-learning based applications for clients across various industries. As an ML Engineer, you will lead the development and integration of machine learning and AI-based software solutions in collaboration with ML Scientists and our clients.

Requirements

• Minimum 2 years of industry experience writing and deploying Python-based applications
• Very strong proficiency in Python
• Experience in packaging custom Python applications
• API Development Proficient in developing RESTful and gRPC APIs
• Experience using FastAPI
• Big Data Experience using PySpark
• DevOps Skills Containerization Proficiency in containerizing applications using Docker and deploying on Kubernetes or cloud-based container services platforms (e.g., ECS)
• Infrastructure as Code Experience defining and deploying infrastructure-as-code with Terraform
• Hands-on experience with AWS services including EKS, ECS, EMR, Batch, Glue, Lambda, and SQS
• Data/ML Experience Strong knowledge of SQL
• Experience integrating with ML models (locally or externally hosted)
• Demonstrated problem solving and quantitative skills, combined with excellent written and verbal communication skills are required

Responsibilities

• Work with machine learning scientists and other engineers to develop custom ML solutions for a variety of industries and use cases
• Build machine learning pipelines from ideation up through prototyping, development, and deployment
• Build data pipelines which can ingest, transform, and export data
• Embed statistical algorithms and machine learning models in cloud-based applications
• Help identify areas of opportunity and improvement within projects
• Collaborate in a fully remote, Agile-like environment using tools like Slack and Git (with a lot of uninterrupted development time)

Benefits

• Competitive salary
• 100%-covered Health insurance for employees, 75%-covered dependents
• Four weeks PTO
• 401(k) with employer contribution matching
• Personalized monthly perks with matched charitable donations
• A 100% remote work environment with highly protected work/life balance