AI/ML Engineer
united it solutionsAustin (TX)
About the role
Role: AI/ML Engineer
Location: Austin TX (100% Onsite)
Job Description:
- 8+ years' experience as AI/ML Engineer
- Work and collaborate with data science and engineering teams to deploy and scale models and algorithms.
- Operationalize complex machine learning models into production including end to end deployment.
- Understand standard Machine Learning algorithms (Regression, Classification) & Natural Language processing concepts (sentiment generation, topic modeling, TFIDF) .Working knowledge of standard ML packages like scikit learn, vader sentiment, Pandas, PySpark.
- Design, Develop and maintain adaptable data pipelines to maintain use case specific data.
- Integrate ML use cases in business pipelines & work closely with upstream & downstream teams to ensure smooth handshake of information.
- Develop & maintain pipelines to generate & publish model performance metrics that can be utilized by Model owners for Model Risk Oversight's model review cadence.
- Support the operationalized models and develop runbooks for maintenance.
Skills: AI/ML, GCP, Python, SQL and experience in SDLC projects
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
More like this