Machine Learning Developer

Tandym Group Logo
Tandym Group
Charlotte, United States
90000 - 125000 USD / Year
  • Production
  • FlexTime
  • FullTime
  • Applications have closed

Requirements

Must have:

We are looking for candidates with 3-7 years of experience in Machine Learning engineering or applied data science. A Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related discipline is required. Candidates should possess hands-on experience with Databricks, MLflow, Spark, and Delta Lake. Proficiency in Python and SQL is essential; familiarity with Scala is considered a plus. Strong skills in frameworks such as scikit-learn, TensorFlow, or PyTorch are expected, alongside knowledge of MLOps principles and tools. We seek individuals with strong problem-solving and analytical skills who can thrive in an agile, collaborative setting, as well as excellent communication abilities suited for both technical and non-technical audiences.

Responsibilities:

As a Machine Learning Engineer, I will entrust you with the following responsibilities: – Designing, constructing, and fine-tuning ML models using Databricks ML tools. – Partnering with data product teams to convert business needs into ML pipelines. – Implementing the deployment and monitoring of models, along with establishing retraining strategies and drift detection. – Crafting and sustaining scalable ETL/ELT pipelines utilizing Databricks, Spark, and Delta Lake. – Engaging in code reviews and knowledge-sharing sessions with cross-functional teams.

Company:

This role is a contract-to-hire opportunity and can be located in Charlotte, Dallas, Richmond, or Raleigh, with the possibility of remote work and about 50% travel required. The work schedule is flexible, and we cover travel expenses. We operate in a hybrid setting, offering some flexibility in work arrangements. Additionally, preference will be given to candidates with experience in cloud platforms such as Azure, AWS, or GCP, and a basic understanding of ML libraries and frameworks. Proficiency in Scala and familiarity with containerization and orchestration tools, as well as knowledge of cloud platform integration, is also valued.

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