Pilot Company - Machine Learning Engineer - Direct Hire [Remote]

MUST BE LOCATED NEAR ATLANTA

This is a hybrid role, so you must be able to come into the office a couple of days a week.

 

Here is the core they are looking for:

Must Haves:      

1. Python
2. End-to-end machine learning projects
3. Experience evaluation and optimizing model performance in development and production
4. Developing and optimizing machine learning infrastructure and pipelines
5. Able to detect feature drift and concept drift

Nice to Haves

1. AWS or Databricks certifications in machine learning
2. Experience working in Databricks

 

Full Job Description

Summary

The purpose of this job is to implement machine learning models into
production by utilizing state-of-the-art tools/algorithms and methodologies
following DevOps and a test-driven development process.

 

Essential Functions

1. Deliver systematic approaches, integrating work into applications and tools with our influence, build and maintain the large-scale analytics
   infrastructure required for the AI projects, and integrate with external IT
   infrastructure/service to provide e2e solutions
2. Leverage an understanding of software architecture and software patterns
   to write scalable, maintainable, well-designed, and future-proof code
3. Design, develop, and maintain the framework for analytical pipeline
4. Design machine learning systems and implement appropriate ML
   algorithms and tools in collaboration with the data science team
5. Implement best MLOps practices for automation, monitoring, scaling, and
   reliability
6. Model behaviors that support the company’s common purpose; ensure
   guests and team members are supported at the highest level
7. Ensure all activities are in compliance with rules, regulations, policies, and
   procedures
8. Complete other duties as assigned

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or any Quantitative field
• Master’s degree preferred
• Proficiency in at least one of the following programming languages:
  Python, C++, or Java
• Minimum 5 years of experience in Data Science, Machine Learning,
  Software Engineering, or another quantitative discipline required
• Minimum 5 years of experience with some, but not all the technologies
  mentioned in the Specialized Knowledge section

Specialized Knowledge

• Experience architecting machine learning pipelines, including designing, and improving infrastructure for ingesting, storing, and transforming data
• Experience with the usage and implementation of CI/CD pipelines using Jenkins, GitHub Actions, TravisCI, or CircleCI
• Experience with scalable distributed systems hosted on cloud providers
• Experience implementing efficient machine learning pipelines at scale by utilizing distributed and/or GPU hardware optimizations methods
• Experience with data ETL processes and both SQL and noSQL databases and manipulating large structured or unstructured datasets for analysis
• Experience training machine learning models by applying feature engineering, model selection, sampling, and model evaluation strategies using Python frameworks such as scikit-learn, Pandas, Pytorch, NumPy, and PySpark
• Experience developing and deploying scalable implementations of model training and model serving using any of the following technologies:
• MLFlow, AWS SageMaker, Triton Inference Server, ONNX RunTime, TorchScript, or TensorFlow RunTime
• Experience with version control systems (e.g., GitHub, GitLab)

Nice to have:

• Some experience implementing neural networks at scale
• Some experience with the Databricks Lakehouse Platform
• Some experience with C++, CUDA, or the NVIDIA RAPIDS suite
• Databricks Certified Associate Developer for Apache Spark 3.0 certification
• Databricks Certified Machine Learning Associate certification

Competencies:

• Ability to lead, coach, mentor and motivate a diverse team; ensure team
  and individual accountability and performance standards are met
• Ability to prioritize, multitask and manage multiple projects successfully in
  a fast-paced and dynamic environment
• Strong organizational skills with attention to detail
• Ability to communicate and interact effectively with different levels of the
  organization to negotiate, problem solve, complete projects and influence
  decision making
• Strong analytical and strategic thinking skills
• Self-motivated with ability to work both independently and within teams
  in order to establish and meet deadlines, goals, and objectives
• Excellent customer service skills