Full-Time Machine Learning Engineer

Amida is currently looking for a Machine Learning Engineer to join our team in either a hybrid or a remote location.

What you will do:

• Research, implement, and deploy machine learning applications
• Collect data from sandboxed hardware environments to build up robust training sets
• Organize, clean, and process data for use in ML applications
• Generalize machine learning approaches into scalable frameworks for deployed training and real-time prediction
• Use model development outcomes to inform future feature and product iterations
• Evaluate, test, and integrate new technologies into our products
• Prototype and iterate solutions with scalability and customer need in mind
• Collaborate with a team of developers, experts, and leaders to meet technical and business needs

Required Skills:

• B.S. or higher in computer science, computer engineering, data science, machine learning or equivalent
• 2-4 years of experience developing Machine Learning Applications in Python using popular Machine Learning and Data Science packages and frameworks such as Keras, Scikit-learn, Pandas, PyTorch, Flask etc.
• Experience defining and conducting data collection and model training experiments as well as interpreting experiment results to inform future investigations
• Proficiency in Python for general programming, scripting, data processing/ingestion, and automation. Other programming languages are a plus
• Excellent written and verbal communication skills.

Desired / Preferred Qualifications:

• Familiarity with a wide range of ML algorithms and approaches
• Experience using Machine Learning tools, deploying models, and deploying software in Azure (certification preferred)
• Experience with Azure Data Lake Storage, Azure Data Factory, Azure SQL DW, Azure Synapse, Databricks, Spark
• Experience developing and deploying software in Linux environments
• Experience working with large data sets in performance focused deployments
• Experience with containerization or cloud-based ML environments
• Experience working with with NLP/LLM tools