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Senior ML Ops Engineer

Dallas, TX, US • Posted 16 hours ago • Updated 16 hours ago

Full Time

Travel Required

Able to Sponsor

On-site

$80,000 - $100,000/yr

Fitment

Dice Job Match Score™

🫥 Flibbertigibetting...

Job Details

Skills

Apache Hadoop
DevOps
Google Cloud Platform
Machine Learning Operations (ML Ops)
Machine Learning (ML)
Kubernetes
Terraform
Python
Java
Docker
Continuous Integration
Continuous Delivery
Apache Spark

Summary

Job Title: Senior ML Ops Engineer

Location: Dallas TX (Onsite)

Job Description:

Must Have - Tech Skills:

Hands on with designing end to end scalable ML system (should have worked on recent projects within last 12 months).
Hands on with implementation of scalable ML system. Proven ownership across entire or partial ML and MLOps lifecycle:

Evaluation Techniques.
Machine Learning Algorithms.
Statistical Modeling.
End to end deployment.
Metric generation.
Model monitoring and deployment.
Prompt Engineering

Hand on with ML Model optimization - quantization, pruning, or speculative decoding etc.
Hand on with ML Model system optimizations ie ability to quickly identify bottlenecks and resolve them from System perspective.
Programming & Frameworks: Hands on and have worked on recent projects (within last 12months) in:

Java

library/dependency management
Package and distribution management
Algorithms

Python
Tensorflow / PyTorch

Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform).
Strong understanding of containerization technologies (e.g., Docker, Kubernetes).

Must Have - Soft Skills:

Good Team worker & good collaborations skills.
Ability to abstract out details, define problem & have clear technical communication.
Ability to lead inter-team communication.
Ability to write crisp and effective documentation.
Ensures that deadlines are met.

Good To Have - Tech Skills:

Google Cloud Platform ML Tech stack.
Experienced with Infrastructure as Code (IaC).
Experience with big data technologies such as Apache Spark or Hadoop.
Stay informed about the ethical implications of machine learning eg: selection bias.
Model Training
Data Analytics - figure out anomalies , skew , discrepancies
Hands on with developing on device ML System.

Good To Have - Soft Skills:

Mentoring and Leadership.
Project Management.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10462843
Position Id: 9015621
Posted 16 hours ago

Contact the job poster

Vemula Sowmya

Recruiter @ Photon

View Profile

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