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Onsite 2-3 days per week 60093
No Sponsorship at this time
Salary 150-170K Bonus
Tech: Azure Machine Learning, Python, SQL, ML Ops
Nice to Haves: GenAI / chatbot, Datalake
Core Responsibilities:
1. Establishing best practices for AI/ML
2. Helping with Deployment
Summary: This Machine Learning Engineer is responsible for developing and deploying AI solutions within core business functions using cloud-native technologies. This role involves ensuring scalability, availability, and efficiency of AI deployments, and establishing best practices in AI operations. Candidates should have cloud-native experience with machine learning engineering and AI platforms in a large-scale environment. Experience operationalizing GenAI applications is not required, but will be an advantage.
Responsibilities:
Design and implement end-to-end machine learning pipelines that are fully integrated within cloud-native architectures, ensuring scalability and robustness.
Work closely with data scientists to operationalize machine learning models on cloud AI platforms, transitioning from experimental prototypes to production-grade solutions.
Optimize data architectures to enhance the performance and scalability of ML systems on cloud platforms: Azure
Lead the integration of ML models into existing and new system architectures, focusing on compatibility and high performance in a cloud environment. This includes designing and implementing robust APIs.
Collaborate with cloud architecture advisors to leverage advanced features of cloud technologies and AI platforms
Establish and evangelize best practices around AI Operations (including MLOps and LLMOps).
Continuously monitor, evaluate, and enhance the performance and efficiency of ML systems deployed on cloud infrastructures.
Skills:
Demonstrated experience with AI platforms on the cloud, such as Azure Machine Learning, Google AI Platform, or AWS SageMaker.
Strong proficiency in using major cloud services (Azure, AWS, GCP) for deploying ML models and managing data pipelines.
Proficient in Python, SQL, and cloud-native technologies such as Kubernetes and Docker.
Experience using Linux OS
Strong problem-solving skills, organizational abilities, and effective communication skills.
Experience operationalizing GenAI applications or assistants.
Full Time
Heavy Civil Construction
$118k-146k (estimate)
06/20/2024
07/18/2024
brilliantmagazine.com
WEST LAKE HILLS, TX
25 - 50
2003
Private
ROBERT B PULLEN SR
<$5M
Heavy Civil Construction
The job skills required for Machine Learning Engineer include AWS, Linux, Kubernetes, Problem Solving, etc. Having related job skills and expertise will give you an advantage when applying to be a Machine Learning Engineer. That makes you unique and can impact how much salary you can get paid. Below are job openings related to skills required by Machine Learning Engineer. Select any job title you are interested in and start to search job requirements.
The following is the career advancement route for Machine Learning Engineer positions, which can be used as a reference in future career path planning. As a Machine Learning Engineer, it can be promoted into senior positions as a Software Engineer IV that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Machine Learning Engineer. You can explore the career advancement for a Machine Learning Engineer below and select your interested title to get hiring information.