Machine Learning Engineer – (Time Series and forecasting experience)

Company:  US Tech Solutions
Location: Seattle
Closing Date: 04/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description

Duration: 9 Months Contract


Must have: Time Series and forecasting experience.


Job Description:

  • Design and develop machine learning models to assist finance and product teams for improved quarterly spend forecasting
  • Develop scalable and efficient data pipelines and processes for training, inferencing and model evaluation for high accuracy
  • Collaborate with engineering teams, finance and product managers in an open, and creative environment.
  • Work closely with Frontend engineers and Software Engineers to present forecasts in a performant and timely manner.



Experience:

  • MS in Math, computer science or AI related field
  • 4+ years of working experience on machine learning, and statistics with focus on forecasting in leading product companies.
  • Proficient with Python, Spark, Databricks, SQL, large scale ML/DL platforms and ML forecasting models
  • Passion for technology, open to interdisciplinary work, and experience in building data-driven services and applications.
  • Excellent written and verbal communication skills


Skills:

Good to have:

  • Understanding of generative machine learning models, including architectures like transformers and popular implementations such as GPT
  • Understand different genAI application development methods.


Education:

BS STEM


About US Tech Solutions:

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit


US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.


Recruiter Details:

Name: Mayur

Email:

Internal Id: 24-20679

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