Senior ML Ops Engineer - Dallas, TX
Fa Ertb Saasfaprod1.fa.ocs.oraclecloud.com.cx 2
Sourced from Fa Ertb Saasfaprod1.fa.ocs.oraclecloud.com.cx 2's careers site · Posting last seen October 31, 2026
Who are we?
For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o.
Must Have - Tech Skills:
2. Hands on with implementation of scalable ML system. Proven ownership across entire or partial ML and MLOps lifecycle:
a. Evaluation Techniques.
b. Machine Learning Algorithms.
c. Statistical Modeling.
d. End to end deployment.
e. Metric generation.
f. Model monitoring and deployment.
g. Prompt Engineering,
3. Hand on with ML Model optimization - quantization, pruning, or speculative decoding etc.
4. Hand on with ML Model system optimizations ie ability to quickly identify bottlenecks and resolve them from System perspective.
5. Programming & Frameworks: Hands on and have worked on recent projects (within last 12months) in:
a. Java
i. library/dependency management
ii. Package and distribution management
iii. Algorithms
b. Python
c. Tensorflow / PyTorch
6. Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform).
7. Strong understanding of containerization technologies (e.g., Docker, Kubernetes).
Must Have - Soft Skills:
2. Ability to abstract out details, define problem & have clear technical communication.
3. Ability to lead inter team communication.
4. Ability to write crisp and effective documentation.
5. Ensures that deadlines are met.
Good To Have - Tech Skills:
2. Experienced with Infrastructure as Code (IaC).
3. Experience with big data technologies such as Apache Spark or Hadoop.
4. Stay informed about the ethical implications of machine learning eg: selection bias.
5. Model Training
7. Hands on with developing on device ML System.
Good To Have - Soft Skills:
1. Mentoring and Leadership.
2. Project Management.
Compensation, Benefits and Duration
Minimum Compensation: USD 51,000
Maximum Compensation: USD 178,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees.
This position is available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
Skills
- scalable ML system design
- scalable ML system implementation
- evaluation techniques
- machine learning algorithms
- statistical modeling
- end-to-end deployment
- metric generation
- model monitoring
- prompt engineering
- model optimization
- quantization
- pruning
- speculative decoding
- system optimization
- Java
- library and dependency management
- package and distribution management
- algorithms
- Python
- TensorFlow
- PyTorch
- DevOps
- CI/CD pipelines
- Terraform
- containerization
- Docker
- Kubernetes
- teamwork
- collaboration
- problem definition
- technical communication
- inter-team communication
- documentation
- deadline management
- GCP ML tech stack
- Infrastructure as Code (IaC)
- Apache Spark
- Hadoop
- ethical implications of machine learning
- selection bias
- model training
- data analytics
- anomaly detection
- skew analysis
- discrepancy analysis
- on-device ML systems
- mentoring
- leadership
- project management
- MLOps
- Machine learning systems
- Model deployment
Summary
Design, implement, optimize, deploy, and monitor scalable machine learning systems across the ML and MLOps lifecycle.
Job title
Senior ML Ops Engineer
Experience level
senior level
Industry
digital modernization
Location
Dallas, TX · On-site
Salary
$51k–$178k
Listed in the job description
Management role
No
- Oct 10, 2026 First posted
- Oct 10, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
Posting history
- Oct 10, 2026 First posted
- Oct 10, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
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