The Role
Design, implement, and own end-to-end scalable ML systems and MLOps lifecycle (deployment, monitoring, metrics). Optimize models and system performance, work with Java/Python and TF/PyTorch, use CI/CD, Terraform, Docker/Kubernetes, lead inter-team communication, document work, and meet deadlines.
Summary Generated by Built In
Greetings Everyone
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:
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
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).
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:
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.
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. GCP 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
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.
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 Required
- Design end-to-end scalable ML systems
- Implement scalable ML systems and own parts of the MLOps lifecycle (evaluation, algorithms, statistical modeling, deployment, metrics, monitoring)
- Prompt engineering
- ML model optimization techniques (quantization, pruning, speculative decoding)
- Identify and resolve ML system bottlenecks and performance issues
- Proficient in Java (library/dependency management, packaging, algorithms)
- Proficient in Python
- Experience with TensorFlow and/or PyTorch
- Knowledge of DevOps principles and tools (CI/CD pipelines, Terraform)
- Strong understanding of containerization technologies (Docker, Kubernetes)
- Good teamwork and collaboration skills
- Ability to abstract details, define problems, and communicate technically
- Ability to lead inter-team communication
- Ability to write crisp and effective documentation
- Ensures that deadlines are met
- GCP ML tech stack experience
- Experience with Infrastructure as Code (IaC)
- Experience with big data technologies (Apache Spark, Hadoop)
- Awareness of ethical implications of ML (e.g., selection bias)
- Experience with model training and on-device ML development
- Data analytics skills to detect anomalies, skew, discrepancies
- Mentoring and leadership
- Project management
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The Company
