Job Opportunity
Machine Learning Engineer – Minneapolis
Minneapolis
Full Time

Job Description

Why consider OPI, and why do people dig working here?

  • Variety of consulting; new technologies, projects, and people on a regular basis.
  • Stability; we’ve been around since 1996 and have a diverse mix of clients and technologies to keep us busy, very busy.  And we keep a bench.  If you’re not on a project, you’re writing software for our internal business functions or you’re learning new technologies.  It’s beneficial to make our consultants as marketable as possible.  That’s good for your career.
  • No politics or management; we don’t get in the way.  Why sit in meetings all day when you can code and be productive?
  • Awesome benefits; free healthcare for your entire family (yes, free), 24 days of PTO + 10 days of sick time, quarterly profit sharing bonuses, you get paid OT, company trips, various quarterly company events, new Macbook Pro’s, free beer/soda, chips, candy, and so much more.
  • You work with the best. Do an Object Partners search on LinkedIn and see the types of talent we hire.  You truly get to work with intelligent, passionate engineers that share the same goal of building great software the right way.
  • Low company overhead. It all means more money back into our consultants pockets (profit sharing) or company trips and events to share in the financial success.

Machine Learning Engineer

As a Machine Learning Engineer, you’ll be working with the latest cloud and technology stacks to help clients implement and mature their modern data and machine learning architecture. You will work with tools like Snowflake, Vertex.AI, AWS Sagemaker, Azure ML, Databricks, and more. With a variety of projects, technologies, and clients, you will constantly be growing, and never bored.

Qualifications

  • At least 4 years of experience as a hands-on software engineer or machine learning engineer
  • At least 1 year of building production-grade data engineering solutions (Example: ETL/ELT, Spark, Azure Data Factory, AWS EMR, GCP Cloud Dataflow/Dataproc, streaming and batch systems)
  • Experience working with Data Pipelines and integrating with ML Pipelines
  • Demonstrated aptitude for problem-solving and creativity
  • Ability to learn new technologies and apply learnings to production-grade solutions
  • Understanding of data engineering and how it plays in Machine Learning Systems
  • Experience with at least one prominent cloud provider (e.g. AWS, Azure, GCP)
  • Strong working knowledge of a ML Framework like TensorFlow, PyTorch, or ONNX
  • Strong development skills in both Java and Python
  • Understanding of CI/CD, automated testing and training, and the MLOps culture
  • Effectively communicate complex technical solutions to a variety of audiences through oral and written mediums

Preferred Skills

  • Production experience with at least one distributed ML system like GCP Vertex.AI, AWS Sagemaker, or Azure ML
  • Production experience with at least one messaging technology like Kafka, AWS Kinesis, Cloud Pub/Sub, or RabbitMQ
  • Production experience integrating with various data sources
  • Production experience of pipeline frameworks like KubeFlow or MLFlow
  • Machine Learning Certification on at least one relevant platform/tool (AWS, Azure, GCP, Databricks)
  • Knowledge on architecting ML Systems using modern ML design patterns
  • Strong working knowledge of data analytics, data validation, visualization, and governance
  • Strong understanding of Deep Learning and ML Concepts
  • Familiarity with CNNs, RNN, LSTMs, and other various Neural Network Architectures
  • Experience working in an agile development framework like Scrum or Kanban
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