Senior ML Ops Engineer

Job Description

Senior ML Ops Engineer

Dallas, TX (Onsite)

Long Term Contract

Client will be discussed during a first Photon Call

Requirement:

1. Hands on with designing end to end scalable ML system (should have worked on recent projects within last 12 months).

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 | library/dependency management | Package and distribution management | 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:

1. Good Team worker & good collaborations 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:

1. Google Cloud Platform ML Tech stack.
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

6. Data Analytics - figure out anomalies , skew , discrepancies
7. Hands on with developing on device ML System